Systems and methods for automatic content remediation notification

ABSTRACT

Systems and methods for automatic content remediation notification are disclosed herein. The system can include memory that can contain a content library database. The system can include a first user device and one or more servers. The one or more servers can: receive a content aggregation creation request from the first user device; identify content information associated with a set of the plurality of data packets; apply a filter request to the set of the plurality of data packets; automatically provide information relating to data packets in the restricted set of data packets to the first user device; receive content aggregate information identifying a content aggregate from the first user device; evaluate the content aggregate according to the metadata associated with the data packets of the content aggregate; and output an indicator of the evaluation result to the first user device.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/443,221, filed on Jan. 6, 2017, and entitled “SYSTEMS AND METHODS FORAUTOMATIC CONTENT REMEDIATION NOTIFICATION”, the entirety of which ishereby incorporated by reference herein.

BACKGROUND

A computer network or data network is a telecommunications network thatallows computers to exchange data. In computer networks, networkedcomputing devices exchange data with each other along network links(data connections). The connections between nodes are established usingeither cable media or wireless media. The best-known computer network isthe Internet.

Network computer devices that originate, route, and terminate the dataare called network nodes. Nodes can include hosts such as personalcomputers, phones, servers as well as networking hardware. Two suchdevices can be said to be networked together when one device is able toexchange information with the other device, whether or not they have adirect connection to each other.

Computer networks differ in the transmission media used to carry theirsignals, the communications protocols to organize network traffic, thenetwork's size, topology, and organizational intent. In most cases,communications protocols are layered on (i.e. work using) other morespecific or more general communications protocols, except for thephysical layer that directly deals with the transmission media.

Notifications can be sent through a computer network. Thesenotifications can be electronic notification and can be receive viae-mail, phone, text message, or fax. Notifications have manyapplications for businesses, governments, schools, and individuals.

BRIEF SUMMARY

One aspect of the present disclosure relates to a system for automaticcontent remediation notification. The system includes memory that caninclude a content library database that includes a plurality of datapackets and metadata associated with each of the data packets, whichmetadata identifies at least one attribute of the associated datapacket. The system includes a first user device including a firstnetwork interface that can exchange data via a communication network anda first I/O subsystem that can convert electrical signals to userinterpretable outputs via a user interface. The system can include asecond user device and one or more servers. In some embodiments, the oneor more servers can: receive a content aggregation creation request fromthe first user device; identify content information associated with aset of the plurality of data packets in response to the receipt of thecontent aggregation creation request; apply a filter request to the setof the plurality of data packets to form a restricted set of data;automatically provide information relating to data packets in therestricted set of data packets to the first user device; receive contentaggregate information identifying a content aggregate from the firstuser device, which content aggregate includes a plurality of datapackets from the restricted set of data packets; evaluate the contentaggregate according to the metadata associated with the data packets ofthe content aggregate; and automatically output an indicator of theevaluation result to the first user device.

In some embodiments, the one or more servers can receive a filterrequest from the first user device, which filter request identifies atleast one attribute as a criterion for inclusion of a data packet withinthe restricted set of data packets. In some embodiments, the filterrequest identifies an intended recipient of the content aggregate. Insome embodiments, the identification of the intended recipient of thecontent aggregate includes identification of one or more attributes ofthe intended recipient of the content aggregate.

In some embodiments, applying the filter request to the set of theplurality of data packets includes identifying a norm group for theintended recipient. In some embodiments, the norm group comprisesincludes data previously gathered from users similar to the intendedrecipient. In some embodiments, evaluating the content aggregateincludes automatically generating a reliability value based on themetadata of the data packets in the content aggregate. In someembodiments, the reliability value can be Cronbach's α. In someembodiments is generated for at least one age group.

In some embodiments, evaluating the content aggregate further includesgenerating supplemental statistical parameters from the norm group data.In some embodiments, the supplemental statistical parameters include amean and a standard deviation. In some embodiments, evaluating thecontent aggregate further includes: generating a content score;comparing the content score to a threshold, which threshold delineatesbetween acceptable and unacceptable content scores; and generating acompliance recommendation when the comparing of the content score to thethreshold indicates that the content score is unacceptable. In someembodiments, the compliance recommendation identifies at least one datapacket for inclusion in the content aggregation. In some embodimentsautomatically outputting the indicator of the evaluation result includesautomatically sending the compliance recommendation to the first userdevice.

One aspect of the present disclosure relates to a method for automaticcontent remediation notification. The method includes: receiving acontent aggregation creation request from the first user device;identifying content information associated with a set of the pluralityof data packets in response to the receipt of the content aggregationcreation request; applying a filter request to the set of the pluralityof data packets to form a restricted set of data; automaticallyproviding information relating to data packets in the restricted set ofdata packets to the first user device; receiving content aggregateinformation identifying a content aggregate from the first user device,which content aggregate, also referred to herein as a contentaggregation, includes a plurality of data packets from the restrictedset of data packets; evaluating the content aggregate according to themetadata associated with the data packets of the content aggregate; andautomatically outputting an indicator of the evaluation result to thefirst user device.

In some embodiments, the method includes receiving a filter request froma first user device, which filter request identifies at least oneattribute as a criterion for inclusion of a data packet within therestricted set of data packets, and which filter request identifies anintended recipient of the content aggregate. In some embodiments, theidentification of the intended recipient of the content aggregateincludes identification of one or more attributes of the intendedrecipient of the content aggregate, and applying the filter request tothe set of the plurality of data packets includes identifying a normgroup for the intended recipient, which norm group includes norm datapreviously gathered from users similar to the intended recipient.

In some embodiments, evaluating the content aggregate includesautomatically generating a reliability value based on the metadata ofthe data packets in the content aggregate and generating supplementalstatistical parameters from the norm group data. In some embodiments,evaluating the content aggregate further includes: generating a contentscore; comparing the content score to a threshold, which thresholddelineates between acceptable and unacceptable content scores; andgenerating a compliance recommendation when the comparing of the contentscore to the threshold indicates that the content score is unacceptable.In some embodiments, the compliance recommendation identifies at leastone data packet for inclusion in the content aggregation, andautomatically outputting the indicator of the evaluation result includesautomatically sending the compliance recommendation to the first userdevice.

Further areas of applicability of the present disclosure will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description and specific examples, whileindicating various embodiments, are intended for purposes ofillustration only and are not intended to necessarily limit the scope ofthe disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing illustrating an example of a contentdistribution network.

FIG. 2 is a block diagram illustrating a computer server and computingenvironment within a content distribution network.

FIG. 3 is a block diagram illustrating an embodiment of one or more datastore servers within a content distribution network.

FIG. 4 is a block diagram illustrating an embodiment of one or morecontent management servers within a content distribution network.

FIG. 5 is a block diagram illustrating the physical and logicalcomponents of a special-purpose computer device within a contentdistribution network.

FIG. 6 is a block diagram illustrating one embodiment of thecommunication network.

FIG. 7 is a block diagram illustrating one embodiment of user device andsupervisor device communication.

FIG. 8 is a schematic illustration of one embodiment of an automaticcontent remediation notification system.

FIG. 9 is a swim lane diagram of one embodiment of a process for contentaggregation creation.

FIG. 10 is a schematic illustration of one embodiment of a managementinterface.

FIG. 11 is a schematic illustration of one embodiment of a form builderuser interface.

FIG. 12 is a schematic illustration of one embodiment of the formbuilder user interface in which content components have been added tothe form.

FIG. 13 is a schematic illustration of one embodiment of the formbuilder user interface in which scoring is being performed.

FIG. 14 is a flowchart illustrating one embodiment of a process forcontent aggregation creation.

FIG. 15 is a flowchart illustrating one embodiment of a process forautomated data tracker delivery.

FIG. 16 is a depiction of one embodiment of a data tracker.

In the appended figures, similar components and/or features may have thesame reference label. Further, various components of the same type maybe distinguished by following the reference label by a dash and a secondlabel that distinguishes among the similar components. If only the firstreference label is used in the specification, the description isapplicable to any one of the similar components having the same firstreference label irrespective of the second reference label.

DETAILED DESCRIPTION

The ensuing description provides illustrative embodiment(s) only and isnot intended to limit the scope, applicability, or configuration of thedisclosure. Rather, the ensuing description of the illustrativeembodiment(s) will provide those skilled in the art with an enablingdescription for implementing a preferred exemplary embodiment. It isunderstood that various changes can be made in the function andarrangement of elements without departing from the spirit and scope asset forth in the appended claims.

With reference now to FIG. 1, a block diagram is shown illustratingvarious components of a content distribution network (CDN) 100 whichimplements and supports certain embodiments and features describedherein. In some embodiments, the content distribution network 100 cancomprise one or several physical components and/or one or severalvirtual components such as, for example, one or several cloud computingcomponents. In some embodiments, the content distribution network 100can comprise a mixture of physical and cloud computing components.

Content distribution network 100 may include one or more contentmanagement servers 102. As discussed below in more detail, contentmanagement servers 102 may be any desired type of server including, forexample, a rack server, a tower server, a miniature server, a bladeserver, a mini rack server, a mobile server, an ultra-dense server, asuper server, or the like, and may include various hardware components,for example, a motherboard, a processing units, memory systems, harddrives, network interfaces, power supplies, etc. Content managementserver 102 may include one or more server farms, clusters, or any otherappropriate arrangement and/or combination or computer servers. Contentmanagement server 102 may act according to stored instructions locatedin a memory subsystem of the server 102, and may run an operatingsystem, including any commercially available server operating systemand/or any other operating systems discussed herein.

The content distribution network 100 may include one or more data storeservers 104, such as database servers and file-based storage systems.The database servers 104 can access data that can be stored on a varietyof hardware components. These hardware components can include, forexample, components forming tier 0 storage, components forming tier 1storage, components forming tier 2 storage, and/or any other tier ofstorage. In some embodiments, tier 0 storage refers to storage that isthe fastest tier of storage in the database server 104, andparticularly, the tier 0 storage is the fastest storage that is not RAMor cache memory. In some embodiments, the tier 0 memory can be embodiedin solid state memory such as, for example, a solid-state drive (SSD)and/or flash memory.

In some embodiments, the tier 1 storage refers to storage that is one orseveral higher performing systems in the memory management system, andthat is relatively slower than tier 0 memory, and relatively faster thanother tiers of memory. The tier 1 memory can be one or several harddisks that can be, for example, high-performance hard disks. These harddisks can be one or both of physically or communicatingly connected suchas, for example, by one or several fiber channels. In some embodiments,the one or several disks can be arranged into a disk storage system, andspecifically can be arranged into an enterprise class disk storagesystem. The disk storage system can include any desired level ofredundancy to protect data stored therein, and in one embodiment, thedisk storage system can be made with grid architecture that createsparallelism for uniform allocation of system resources and balanced datadistribution.

In some embodiments, the tier 2 storage refers to storage that includesone or several relatively lower performing systems in the memorymanagement system, as compared to the tier 1 and tier 2 storages. Thus,tier 2 memory is relatively slower than tier 1 and tier 0 memories. Tier2 memory can include one or several SATA-drives or one or severalNL-SATA drives.

In some embodiments, the one or several hardware and/or softwarecomponents of the database server 104 can be arranged into one orseveral storage area networks (SAN), which one or several storage areanetworks can be one or several dedicated networks that provide access todata storage, and particularly that provides access to consolidated,block level data storage. A SAN typically has its own network of storagedevices that are generally not accessible through the local area network(LAN) by other devices. The SAN allows access to these devices in amanner such that these devices appear to be locally attached to the userdevice.

Data stores 104 may comprise stored data relevant to the functions ofthe content distribution network 100. Illustrative examples of datastores 104 that may be maintained in certain embodiments of the contentdistribution network 100 are described below in reference to FIG. 3. Insome embodiments, multiple data stores may reside on a single server104, either using the same storage components of server 104 or usingdifferent physical storage components to assure data security andintegrity between data stores. In other embodiments, each data store mayhave a separate dedicated data store server 104.

Content distribution network 100 also may include one or more userdevices 106 and/or supervisor devices 110. User devices 106 andsupervisor devices 110 may display content received via the contentdistribution network 100, and may support various types of userinteractions with the content. User devices 106 and supervisor devices110 may include mobile devices such as smartphones, tablet computers,personal digital assistants, and wearable computing devices. Such mobiledevices may run a variety of mobile operating systems, and may beenabled for Internet, e-mail, short message service (SMS), Bluetooth®,mobile radio-frequency identification (M-RFID), and/or othercommunication protocols. Other user devices 106 and supervisor devices110 may be general purpose personal computers or special-purposecomputing devices including, by way of example, personal computers,laptop computers, workstation computers, projection devices, andinteractive room display systems. Additionally, user devices 106 andsupervisor devices 110 may be any other electronic devices, such as athin-client computers, an Internet-enabled gaming systems, business orhome appliances, and/or a personal messaging devices, capable ofcommunicating over network(s) 120.

In different contexts of content distribution networks 100, user devices106 and supervisor devices 110 may correspond to different types ofspecialized devices, for example, student devices and teacher devices inan educational network, employee devices and presentation devices in acompany network, different gaming devices in a gaming network, etc. Insome embodiments, user devices 106 and supervisor devices 110 mayoperate in the same physical location 107, such as a classroom orconference room. In such cases, the devices may contain components thatsupport direct communications with other nearby devices, such as awireless transceivers and wireless communications interfaces, Ethernetsockets or other Local Area Network (LAN) interfaces, etc. In otherimplementations, the user devices 106 and supervisor devices 110 neednot be used at the same location 107, but may be used in remotegeographic locations in which each user device 106 and supervisor device110 may use security features and/or specialized hardware (e.g.,hardware-accelerated SSL and HTTPS, WS-Security, firewalls, etc.) tocommunicate with the content management server 102 and/or other remotelylocated user devices 106. Additionally, different user devices 106 andsupervisor devices 110 may be assigned different designated roles, suchas presenter devices, teacher devices, administrator devices, or thelike, and in such cases the different devices may be provided withadditional hardware and/or software components to provide content andsupport user capabilities not available to the other devices.

The content distribution network 100 also may include a privacy server108 that maintains private user information at the privacy server 108while using applications or services hosted on other servers. Forexample, the privacy server 108 may be used to maintain private data ofa user within one jurisdiction even though the user is accessing anapplication hosted on a server (e.g., the content management server 102)located outside the jurisdiction. In such cases, the privacy server 108may intercept communications between a user device 106 or supervisordevice 110 and other devices that include private user information. Theprivacy server 108 may create a token or identifier that does notdisclose the private information and may use the token or identifierwhen communicating with the other servers and systems, instead of usingthe user's private information.

As illustrated in FIG. 1, the content management server 102 may be incommunication with one or more additional servers, such as a contentserver 112, a user data server 112, and/or an administrator server 116.Each of these servers may include some or all of the same physical andlogical components as the content management server(s) 102, and in somecases, the hardware and software components of these servers 112-116 maybe incorporated into the content management server(s) 102, rather thanbeing implemented as separate computer servers.

Content server 112 may include hardware and software components togenerate, store, and maintain the content resources for distribution touser devices 106 and other devices in the network 100. For example, incontent distribution networks 100 used for professional training andeducational purposes, content server 112 may include data stores oftraining materials, presentations, plans, syllabi, reviews, evaluations,interactive programs and simulations, course models, course outlines,and various training interfaces that correspond to different materialsand/or different types of user devices 106. In content distributionnetworks 100 used for media distribution, interactive gaming, and thelike, a content server 112 may include media content files such asmusic, movies, television programming, games, and advertisements.

User data server 114 may include hardware and software components thatstore and process data for multiple users relating to each user'sactivities and usage of the content distribution network 100. Forexample, the content management server 102 may record and track eachuser's system usage, including their user device 106, content resourcesaccessed, and interactions with other user devices 106. This data may bestored and processed by the user data server 114, to support usertracking and analysis features. For instance, in the professionaltraining and educational contexts, the user data server 114 may storeand analyze each user's training materials viewed, presentationsattended, courses completed, interactions, evaluation results, and thelike. The user data server 114 may also include a repository foruser-generated material, such as evaluations and tests completed byusers, and documents and assignments prepared by users. In the contextof media distribution and interactive gaming, the user data server 114may store and process resource access data for multiple users (e.g.,content titles accessed, access times, data usage amounts, gaminghistories, user devices and device types, etc.).

Administrator server 116 may include hardware and software components toinitiate various administrative functions at the content managementserver 102 and other components within the content distribution network100. For example, the administrator server 116 may monitor device statusand performance for the various servers, data stores, and/or userdevices 106 in the content distribution network 100. When necessary, theadministrator server 116 may add or remove devices from the network 100,and perform device maintenance such as providing software updates to thedevices in the network 100. Various administrative tools on theadministrator server 116 may allow authorized users to set user accesspermissions to various content resources, monitor resource usage byusers and devices 106, and perform analyses and generate reports onspecific network users and/or devices (e.g., resource usage trackingreports, training evaluations, etc.).

The content distribution network 100 may include one or morecommunication networks 120. Although only a single network 120 isidentified in FIG. 1, the content distribution network 100 may includeany number of different communication networks between any of thecomputer servers and devices shown in FIG. 1 and/or other devicesdescribed herein. Communication networks 120 may enable communicationbetween the various computing devices, servers, and other components ofthe content distribution network 100. As discussed below, variousimplementations of content distribution networks 100 may employdifferent types of networks 120, for example, computer networks,telecommunications networks, wireless networks, and/or any combinationof these and/or other networks.

The content distribution network 100 may include one or severalnavigation systems or features including, for example, the GlobalPositioning System (“GPS”), GALILEO, or the like, or location systems orfeatures including, for example, one or several transceivers that candetermine location of the one or several components of the contentdistribution network 100 via, for example, triangulation. All of theseare depicted as navigation system 122.

In some embodiments, navigation system 122 can include or severalfeatures that can communicate with one or several components of thecontent distribution network 100 including, for example, with one orseveral of the user devices 106 and/or with one or several of thesupervisor devices 110. In some embodiments, this communication caninclude the transmission of a signal from the navigation system 122which signal is received by one or several components of the contentdistribution network 100 and can be used to determine the location ofthe one or several components of the content distribution network 100.

With reference to FIG. 2, an illustrative distributed computingenvironment 200 is shown including a computer server 202, four clientcomputing devices 206, and other components that may implement certainembodiments and features described herein. In some embodiments, theserver 202 may correspond to the content management server 102 discussedabove in FIG. 1, and the client computing devices 206 may correspond tothe user devices 106. However, the computing environment 200 illustratedin FIG. 2 may correspond to any other combination of devices and serversconfigured to implement a client-server model or other distributedcomputing architecture.

Client devices 206 may be configured to receive and execute clientapplications over one or more networks 220. Such client applications maybe web browser based applications and/or standalone softwareapplications, such as mobile device applications. Server 202 may becommunicatively coupled with the client devices 206 via one or morecommunication networks 220. Client devices 206 may receive clientapplications from server 202 or from other application providers (e.g.,public or private application stores). Server 202 may be configured torun one or more server software applications or services, for example,web-based or cloud-based services, to support content distribution andinteraction with client devices 206. Users operating client devices 206may in turn utilize one or more client applications (e.g., virtualclient applications) to interact with server 202 to utilize the servicesprovided by these components.

Various different subsystems and/or components 204 may be implemented onserver 202. Users operating the client devices 206 may initiate one ormore client applications to use services provided by these subsystemsand components. The subsystems and components within the server 202 andclient devices 206 may be implemented in hardware, firmware, software,or combinations thereof. Various different system configurations arepossible in different distributed computing systems 200 and contentdistribution networks 100. The embodiment shown in FIG. 2 is thus oneexample of a distributed computing system and is not intended to belimiting.

Although exemplary computing environment 200 is shown with four clientcomputing devices 206, any number of client computing devices may besupported. Other devices, such as specialized sensor devices, etc., mayinteract with client devices 206 and/or server 202.

As shown in FIG. 2, various security and integration components 208 maybe used to send and manage communications between the server 202 anduser devices 206 over one or more communication networks 220. Thesecurity and integration components 208 may include separate servers,such as web servers and/or authentication servers, and/or specializednetworking components, such as firewalls, routers, gateways, loadbalancers, and the like. In some cases, the security and integrationcomponents 208 may correspond to a set of dedicated hardware and/orsoftware operating at the same physical location and under the controlof same entities as server 202. For example, components 208 may includeone or more dedicated web servers and network hardware in a datacenteror a cloud infrastructure. In other examples, the security andintegration components 208 may correspond to separate hardware andsoftware components which may be operated at a separate physicallocation and/or by a separate entity.

Security and integration components 208 may implement various securityfeatures for data transmission and storage, such as authenticating usersand restricting access to unknown or unauthorized users. In variousimplementations, security and integration components 208 may provide,for example, a file-based integration scheme or a service-basedintegration scheme for transmitting data between the various devices inthe content distribution network 100. Security and integrationcomponents 208 also may use secure data transmission protocols and/orencryption for data transfers, for example, File Transfer Protocol(FTP), Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy(PGP) encryption.

In some embodiments, one or more web services may be implemented withinthe security and integration components 208 and/or elsewhere within thecontent distribution network 100. Such web services, includingcross-domain and/or cross-platform web services, may be developed forenterprise use in accordance with various web service standards, such asRESTful web services (i.e., services based on the Representation StateTransfer (REST) architectural style and constraints), and/or webservices designed in accordance with the Web Service Interoperability(WS-I) guidelines. Some web services may use the Secure Sockets Layer(SSL) or Transport Layer Security (TLS) protocol to provide secureconnections between the server 202 and user devices 206. SSL or TLS mayuse HTTP or HTTPS to provide authentication and confidentiality. Inother examples, web services may be implemented using REST over HTTPSwith the OAuth open standard for authentication, or using theWS-Security standard which provides for secure SOAP messages using XMLencryption. In other examples, the security and integration components208 may include specialized hardware for providing secure web services.For example, security and integration components 208 may include securenetwork appliances having built-in features such as hardware-acceleratedSSL and HTTPS, WS-Security, and firewalls. Such specialized hardware maybe installed and configured in front of any web servers, so that anyexternal devices may communicate directly with the specialized hardware.

Communication network(s) 220 may be any type of network familiar tothose skilled in the art that can support data communications using anyof a variety of commercially-available protocols, including withoutlimitation, TCP/IP (transmission control protocol/Internet protocol),SNA (systems network architecture), IPX (Internet packet exchange),Secure Sockets Layer (SSL) or Transport Layer Security (TLS) protocols,Hyper Text Transfer Protocol (HTTP) and Secure Hyper Text TransferProtocol (HTTPS), Bluetooth®, Near Field Communication (NFC), and thelike. Merely by way of example, network(s) 220 may be local areanetworks (LAN), such as one based on Ethernet, Token-Ring and/or thelike. Network(s) 220 also may be wide-area networks, such as theInternet. Networks 220 may include telecommunication networks such as apublic switched telephone networks (PSTNs), or virtual networks such asan intranet or an extranet. Infrared and wireless networks (e.g., usingthe Institute of Electrical and Electronics (IEEE) 802.11 protocol suiteor other wireless protocols) also may be included in networks 220.

Computing environment 200 also may include one or more data stores 210and/or back-end servers 212. In certain examples, the data stores 210may correspond to data store server(s) 104 discussed above in FIG. 1,and back-end servers 212 may correspond to the various back-end servers112-116. Data stores 210 and servers 212 may reside in the samedatacenter or may operate at a remote location from server 202. In somecases, one or more data stores 210 may reside on a non-transitorystorage medium within the server 202. Other data stores 210 and back-endservers 212 may be remote from server 202 and configured to communicatewith server 202 via one or more networks 220. In certain embodiments,data stores 210 and back-end servers 212 may reside in a storage-areanetwork (SAN), or may use storage-as-a-service (STaaS) architecturalmodel.

With reference to FIG. 3, an illustrative set of data stores and/or datastore servers is shown, corresponding to the data store servers 104 ofthe content distribution network 100 discussed above in FIG. 1. One ormore individual data stores 301-311 may reside in storage on a singlecomputer server 104 (or a single server farm or cluster) under thecontrol of a single entity, or may reside on separate servers operatedby different entities and/or at remote locations. In some embodiments,data stores 301-311 may be accessed by the content management server 102and/or other devices and servers within the network 100 (e.g., userdevices 106, supervisor devices 110, administrator servers 116, etc.).Access to one or more of the data stores 301-311 may be limited ordenied based on the processes, user credentials, and/or devicesattempting to interact with the data store.

The paragraphs below describe examples of specific data stores that maybe implemented within some embodiments of a content distribution network100. It should be understood that the below descriptions of data stores301-311, including their functionality and types of data stored therein,are illustrative and non-limiting. Data stores server architecture,design, and the execution of specific data stores 301-311 may depend onthe context, size, and functional requirements of a content distributionnetwork 100. For example, in content distribution systems 100 used forprofessional training and educational purposes, separate databases orfile-based storage systems may be implemented in data store server(s)104 to store trainee and/or student data, trainer and/or professor data,training module data and content descriptions, training results,evaluation data, and the like. In contrast, in content distributionsystems 100 used for media distribution from content providers tosubscribers, separate data stores may be implemented in data storesserver(s) 104 to store listings of available content titles anddescriptions, content title usage statistics, subscriber profiles,account data, payment data, network usage statistics, etc.

A user profile data store 301, also referred to herein as a user profiledatabase 301, may include information relating to the end users withinthe content distribution network 100. This information may include usercharacteristics such as the user names, access credentials (e.g., loginsand passwords), user preferences, and information relating to anyprevious user interactions within the content distribution network 100(e.g., requested content, posted content, content modules completed,training scores or evaluations, other associated users, etc.). In someembodiments, this information can relate to one or several individualend users such as, for example, one or several students, teachers,administrators, or the like, and in some embodiments, this informationcan relate to one or several institutional end users such as, forexample, one or several schools, groups of schools such as one orseveral school districts, one or several colleges, one or severaluniversities, one or several training providers, or the like. In someembodiments, this information can identify one or several usermemberships in one or several groups such as, for example, a student'smembership in a university, school, program, grade, course, class, orthe like.

The user profile database 301 can include information relating to auser's status, location, or the like. This information can identify, forexample, a device a user is using, the location of that device, or thelike. In some embodiments, this information can be generated based onany location detection technology including, for example, a navigationsystem 122, or the like.

Information relating to the user's status can identify, for example,logged-in status information that can indicate whether the user ispresently logged-in to the content distribution network 100 and/orwhether the log-in-is active. In some embodiments, the informationrelating to the user's status can identify whether the user is currentlyaccessing content and/or participating in an activity from the contentdistribution network 100.

In some embodiments, information relating to the user's status canidentify, for example, one or several attributes of the user'sinteraction with the content distribution network 100, and/or contentdistributed by the content distribution network 100. This can includedata identifying the user's interactions with the content distributionnetwork 100, the content consumed by the user through the contentdistribution network 100, or the like. In some embodiments, this caninclude data identifying the type of information accessed through thecontent distribution network 100 and/or the type of activity performedby the user via the content distribution network 100, the lapsed timesince the last time the user accessed content and/or participated in anactivity from the content distribution network 100, or the like. In someembodiments, this information can relate to a content program comprisingan aggregate of data, content, and/or activities, and can identify, forexample, progress through the content program, or through the aggregateof data, content, and/or activities forming the content program. In someembodiments, this information can track, for example, the amount of timesince participation in and/or completion of one or several types ofactivities, the amount of time since communication with one or severalsupervisors and/or supervisor devices 110, or the like.

In some embodiments in which the one or several end users areindividuals, and specifically are students, the user profile database301 can further include information relating to these students' academicand/or educational history. This information can identify one or severalcourses of study that the student has initiated, completed, and/orpartially completed, as well as grades received in those courses ofstudy. In some embodiments, the student's academic and/or educationalhistory can further include information identifying student performanceon one or several tests, quizzes, and/or assignments. In someembodiments, this information can be stored in a tier of memory that isnot the fastest memory in the content delivery network 100.

The user profile database 301 can include information relating to one orseveral student learning preferences. In some embodiments, for example,the user, also referred to herein as the student or the student-user mayhave one or several preferred learning styles, one or several mosteffective learning styles, and/or the like. In some embodiments, thestudent's learning style can be any learning style describing how thestudent best learns or how the student prefers to learn. In oneembodiment, these learning styles can include, for example,identification of the student as an auditory learner, as a visuallearner, and/or as a tactile learner. In some embodiments, the dataidentifying one or several student learning styles can include dataidentifying a learning style based on the student's educational historysuch as, for example, identifying a student as an auditory learner whenthe student has received significantly higher grades and/or scores onassignments and/or in courses favorable to auditory learners. In someembodiments, this information can be stored in a tier of memory that isnot the fastest memory in the content delivery network 100.

In some embodiments, the user profile data store 301 can further includeinformation identifying one or several user skill levels. In someembodiments, these one or several user skill levels can identify a skilllevel determined based on past performance by the user interacting withthe content delivery network 100, and in some embodiments, these one orseveral user skill levels can identify a predicted skill leveldetermined based on past performance by the user interacting with thecontent delivery network 100 and one or several predictive models.

The user profile database 301 can further include information relatingto one or several teachers and/or instructors who are responsible fororganizing, presenting, and/or managing the presentation of informationto the student. In some embodiments, user profile database 301 caninclude information identifying courses and/or subjects that have beentaught by the teacher, data identifying courses and/or subjectscurrently taught by the teacher, and/or data identifying courses and/orsubjects that will be taught by the teacher. In some embodiments, thiscan include information relating to one or several teaching styles ofone or several teachers. In some embodiments, the user profile database301 can further include information indicating past evaluations and/orevaluation reports received by the teacher. In some embodiments, theuser profile database 301 can further include information relating toimprovement suggestions received by the teacher, training received bythe teacher, continuing education received by the teacher, and/or thelike. In some embodiments, this information can be stored in a tier ofmemory that is not the fastest memory in the content delivery network100.

An accounts data store 302, also referred to herein as an accountsdatabase 302, may generate and store account data for different users invarious roles within the content distribution network 100. For example,accounts may be created in an accounts data store 302 for individual endusers, supervisors, administrator users, and entities such as companiesor educational institutions. Account data may include account types,current account status, account characteristics, and any parameters,limits, restrictions associated with the accounts.

A content library data store 303, also referred to herein as a contentlibrary database 303, may include information describing the individualcontent items (or content resources or data packets) available via thecontent distribution network 100. In some embodiments, these datapackets in the content library database 303 can be linked to form anobject network. In some embodiments, these data packets can be linked inthe object network according to one or several prerequisiterelationships that can, for example, identify the relative hierarchyand/or difficulty of the data objects. In some embodiments, thishierarchy of data objects can be generated by the content distributionnetwork 100 according to user experience with the object network, and insome embodiments, this hierarchy of data objects can be generated basedon one or several existing and/or external hierarchies such as, forexample, a syllabus, a table of contents, or the like. In someembodiments, for example, the object network can correspond to asyllabus such that content for the syllabus is embodied in the objectnetwork.

In some embodiments, the content library database 303 can include aplurality of content components. The content components can, in someembodiments, comprise one or several tasks, questions, activities, orthe like that can be combined together to create a single piece ofcontent, also referred to herein as a content aggregation or form, suchas, for example, a single assignment, quiz, test, or evaluation. In someembodiments, these single content components can be each associated withinformation. This information can be generated from user interactionwith the content of the single components. In some embodiments, thisinformation can, for example, characterize a reliability of the singleitem, a difficult of the single item, a differentiation of the singleitem, one or several averages of the single item, one or severalstandard deviations of the single item, or the like. In someembodiments, the differentiation of the single item can characterize thedegree to which correctly or incorrectly responding to the itemdelineates between skill levels, attribute levels, or the like. In someembodiments, information associated with single items can be used todetermine a reliability of a combination of multiple items.

In some embodiments, the content library database 303 can comprise oneor several forms that can each include a plurality content components.In some embodiments, these forms can be created by a user of the CDN 100from the content components stored in the content library database 303.In some embodiments, some or all of these one or several forms can becharacterized by, for example, one or several scores or statisticalmeasures. These scores or statistical measures can include a reliabilitycoefficient such as, for example, a Cronbach's α, an error score orvalue such as, for example, a standard error of measurement (SEM) score,or the like. In some embodiments, one or several of these scores can becalculated based on the information associated with each of the contentcomponents. In some embodiments, these one or several scores of the formcan be calculated in real-time and in some embodiments, one or severalscores for alternative forms can be calculated to allow therecommendation of one or several content components for inclusion in theform and/or for removal from the form. In some embodiments, these one orseveral scores can vary based on one or several attributes of theintended recipient and/or recipients of the form. These one or severalattributes can include, for example, gender, age, education,intelligence, or the like.

In some embodiments, the content library data store 303 can comprise asyllabus, a schedule, or the like. In some embodiments, the syllabus orschedule can identify one or several tasks and/or events relevant to theuser. In some embodiments, for example, when the user is a member of agroup such as, a section or a class, these tasks and/or events relevantto the user can identify one or several assignments, quizzes, exams, orthe like.

In some embodiments, the library data store 303 may include metadata,properties, and other characteristics associated with the contentresources stored in the content server 112. Such data may identify oneor more aspects or content attributes of the associated contentresources, for example, subject matter, access level, or skill level ofthe content resources, license attributes of the content resources(e.g., any limitations and/or restrictions on the licensable use and/ordistribution of the content resource), price attributes of the contentresources (e.g., a price and/or price structure for determining apayment amount for use or distribution of the content resource), ratingattributes for the content resources (e.g., data indicating theevaluation or effectiveness of the content resource), and the like. Insome embodiments, the library data store 303 may be configured to allowupdating of content metadata or properties, and to allow the additionand/or removal of information relating to the content resources. Forexample, content relationships may be implemented as graph structures,which may be stored in the library data store 303 or in an additionalstore for use by selection algorithms along with the other metadata.

In some embodiments, the content library data store 303 can containinformation used in evaluating responses received from users. In someembodiments, for example, a user can receive content from the contentdistribution network 100 and can, subsequent to receiving that content,provide a response to the received content. In some embodiments, forexample, the received content can comprise one or several questions,prompts, or the like, and the response to the received content cancomprise an answer to those one or several questions, prompts, or thelike. In some embodiments, information, referred to herein as“comparative data,” from the content library data store 303 can be usedto determine whether the responses are the correct and/or desiredresponses.

In some embodiments, the content library database 303 and/or the userprofile database 301 can comprise an aggregation network also referredto herein as a content network are content aggregation network. Theaggregation network can comprise a plurality of content aggregationsthat can be linked together by, for example: creation by common user;relation to a common subject, topic, skill, or the like; creation from acommon set of source material such as source data packets; or the like.In some embodiments, the content aggregation can comprise a grouping ofcontent comprising the presentation portion that can be provided to theuser in the form of, for example, a flash card and an extraction portionthat can comprise the desired response to the presentation portion suchas for example, an answer to a flash card. In some embodiments, one orseveral content aggregations can be generated by the contentdistribution network 100 and can be related to one or several datapackets they can be, for example, organized in object network. In someembodiments, the one or several content aggregations can be each createdfrom content stored in one or several of the data packets.

In some embodiments, the content aggregations located in the contentlibrary database 303 and/or the user profile database 301 can beassociated with a user-creator of those content aggregations. In someembodiments, access to content aggregations can vary based on, forexample, whether a user created the content aggregations. In someembodiments, the content library database 303 and/or the user profiledatabase 301 can comprise a database of content aggregations associatedwith a specific user, and in some embodiments, the content librarydatabase 303 and/or the user profile database 301 can comprise aplurality of databases of content aggregations that are each associatedwith a specific user. In some embodiments, these databases of contentaggregations can include content aggregations created by their specificuser and in some embodiments, these databases of content aggregationscan further include content aggregations selected for inclusion by theirspecific user and/or a supervisor of that specific user. In someembodiments, these content aggregations can be arranged and/or linked ina hierarchical relationship similar to the data packets in the objectnetwork and/or linked to the object network in the object network or thetasks or skills associated with the data packets in the object networkor the syllabus or schedule.

In some embodiments, the content aggregation network, and the contentaggregations forming the content aggregation network can be organizedaccording to the object network and/or the hierarchical relationshipsembodied in the object network. In some embodiments, the contentaggregation network, and/or the content aggregations forming the contentaggregation network can be organized according to one or several tasksidentified in the syllabus, schedule or the like.

A pricing data store 304 may include pricing information and/or pricingstructures for determining payment amounts for providing access to thecontent distribution network 100 and/or the individual content resourceswithin the network 100. In some cases, pricing may be determined basedon a user's access to the content distribution network 100, for example,a time-based subscription fee, or pricing based on network usage and. Inother cases, pricing may be tied to specific content resources. Certaincontent resources may have associated pricing information, whereas otherpricing determinations may be based on the resources accessed, theprofiles and/or accounts of the user, and the desired level of access(e.g., duration of access, network speed, etc.). Additionally, thepricing data store 304 may include information relating to compilationpricing for groups of content resources, such as group prices and/orprice structures for groupings of resources.

A license data store 305 may include information relating to licensesand/or licensing of the content resources within the contentdistribution network 100. For example, the license data store 305 mayidentify licenses and licensing terms for individual content resourcesand/or compilations of content resources in the content server 112, therights holders for the content resources, and/or common or large-scaleright holder information such as contact information for rights holdersof content not included in the content server 112.

A content access data store 306 may include access rights and securityinformation for the content distribution network 100 and specificcontent resources. For example, the content access data store 306 mayinclude login information (e.g., user identifiers, logins, passwords,etc.) that can be verified during user login attempts to the network100. The content access data store 306 also may be used to storeassigned user roles and/or user levels of access. For example, a user'saccess level may correspond to the sets of content resources and/or theclient or server applications that the user is permitted to access.Certain users may be permitted or denied access to certain applicationsand resources based on their subscription level, training program,course/grade level, etc. Certain users may have supervisory access overone or more end users, allowing the supervisor to access all or portionsof the end user's content, activities, evaluations, etc. Additionally,certain users may have administrative access over some users and/or someapplications in the content management network 100, allowing such usersto add and remove user accounts, modify user access permissions, performmaintenance updates on software and servers, etc.

A source data store 307 may include information relating to the sourceof the content resources available via the content distribution network.For example, a source data store 307 may identify the authors andoriginating devices of content resources, previous pieces of data and/orgroups of data originating from the same authors or originating devices,and the like.

An evaluation data store 308 may include information used to direct theevaluation of users and content resources in the content managementnetwork 100. In some embodiments, the evaluation data store 308 maycontain, for example, the analysis criteria and the analysis guidelinesfor evaluating users (e.g., trainees/students, gaming users, mediacontent consumers, etc.) and/or for evaluating the content resources inthe network 100. The evaluation data store 308 also may includeinformation relating to evaluation processing tasks, for example, theidentification of users and user devices 106 that have received certaincontent resources or accessed certain applications, the status ofevaluations or evaluation histories for content resources, users, orapplications, and the like. Evaluation criteria may be stored in theevaluation data store 308 including data and/or instructions in the formof one or several electronic rubrics or scoring guides for use in theevaluation of the content, users, or applications. The evaluation datastore 308 also may include past evaluations and/or evaluation analysesfor users, content, and applications, including relative rankings,characterizations, explanations, and the like.

A model data store 309, also referred to herein as a model database 309can store information relating to one or several predictive models. Insome embodiments, these can include one or several evidence models, riskmodels, skill models, or the like. In some embodiments, an evidencemodel can be a mathematically-based statistical model. The evidencemodel can be based on, for example, Item Response Theory (IRT), BayesianNetwork (Bayes net), Performance Factor Analysis (PFA), or the like. Theevidence model can, in some embodiments, be customizable to a userand/or to one or several content items. Specifically, one or severalinputs relating to the user and/or to one or several content items canbe inserted into the evidence model. These inputs can include, forexample, one or several measures of user skill level, one or severalmeasures of content item difficulty and/or skill level, or the like. Thecustomized evidence model can then be used to predict the likelihood ofthe user providing desired or undesired responses to one or several ofthe content items.

In some embodiments, the risk models can include one or several modelsthat can be used to calculate one or several model function values. Insome embodiments, these one or several model function values can be usedto calculate a risk probability, which risk probability can characterizethe risk of a user such as a student-user failing to achieve a desiredoutcome such as, for example, failing to correctly respond to one orseveral data packets, failure to achieve a desired level of completionof a program, for example in a pre-defined time period, failure toachieve a desired learning outcome, or the like. In some embodiments,the risk probability can identify the risk of the student-user failingto complete 60% of the program.

In some embodiments, these models can include a plurality of modelfunctions including, for example, a first model function, a second modelfunction, a third model function, and a fourth model function. In someembodiments, some or all of the model functions can be associated with aportion of the program such as, for example a completion stage and/orcompletion status of the program. In one embodiment, for example, thefirst model function can be associated with a first completion status,the second model function can be associated with a second completionstatus, the third model function can be associated with a thirdcompletion status, and the fourth model function can be associated witha fourth completion status. In some embodiments, these completionstatuses can be selected such that some or all of these completionstatuses are less than the desired level of completion of the program.Specifically, in some embodiments, these completion status can beselected to all be at less than 60% completion of the program, and morespecifically, in some embodiments, the first completion status can be at20% completion of the program, the second completion status can be at30% completion of the program, the third completion status can be at 40%completion of the program, and the fourth completion status can be at50% completion of the program. Similarly, any desired number of modelfunctions can be associated with any desired number of completionstatuses.

In some embodiments, a model function can be selected from the pluralityof model functions based on a student-user's progress through a program.In some embodiments, the student-user's progress can be compared to oneor several status trigger thresholds, each of which status triggerthresholds can be associated with one or more of the model functions. Ifone of the status triggers is triggered by the student-user's progress,the corresponding one or several model functions can be selected.

The model functions can comprise a variety of types of models and/orfunctions. In some embodiments, each of the model functions outputs afunction value that can be used in calculating a risk probability. Thisfunction value can be calculated by performing one or severalmathematical operations on one or several values indicative of one orseveral user attributes and/or user parameters, also referred to hereinas program status parameters. In some embodiments, each of the modelfunctions can use the same program status parameters, and in someembodiments, the model functions can use different program statusparameters. In some embodiments, the model functions use differentprogram status parameters when at least one of the model functions usesat least one program status parameter that is not used by others of themodel functions.

In some embodiments, a skill model can comprise a statistical modelidentifying a predictive skill level of one or several students. In someembodiments, this model can identify a single skill level of a studentand/or a range of possible skill levels of a student. In someembodiments, this statistical model can identify a skill level of astudent-user and an error value or error range associated with thatskill level. In some embodiments, the error value can be associated witha confidence interval determined based on a confidence level. Thus, insome embodiments, as the number of student interactions with the contentdistribution network increases, the confidence level can increase andthe error value can decrease such that the range identified by the errorvalue about the predicted skill level is smaller.

A threshold database 310, also referred to herein as a thresholddatabase, can store one or several threshold values. These one orseveral threshold values can delineate between states or conditions. Inone exemplary embodiments, for example, a threshold value can delineatebetween an acceptable user performance and an unacceptable userperformance, between content appropriate for a user and content that isinappropriate for a user, between risk levels, or the like.

In addition to the illustrative data stores described above, data storeserver(s) 104 (e.g., database servers, file-based storage servers, etc.)may include one or more external data aggregators 311. External dataaggregators 311 may include third-party data sources accessible to thecontent management network 100, but not maintained by the contentmanagement network 100. External data aggregators 311 may include anyelectronic information source relating to the users, content resources,or applications of the content distribution network 100. For example,external data aggregators 311 may be third-party data stores containingdemographic data, education related data, consumer sales data, healthrelated data, and the like. Illustrative external data aggregators 311may include, for example, social networking web servers, public recordsdata stores, learning management systems, educational institutionservers, business servers, consumer sales data stores, medical recorddata stores, etc. Data retrieved from various external data aggregators311 may be used to verify and update user account information, suggestuser content, and perform user and content evaluations.

With reference now to FIG. 4, a block diagram is shown illustrating anembodiment of one or more content management servers 102 within acontent distribution network 100. In such an embodiment, contentmanagement server 102 performs internal data gathering and processing ofstreamed content along with external data gathering and processing.Other embodiments could have either all external or all internal datagathering. This embodiment allows reporting timely information thatmight be of interest to the reporting party or other parties. In thisembodiment, the content management server 102 can monitor gatheredinformation from several sources to allow it to make timely businessand/or processing decisions based upon that information. For example,reports of user actions and/or responses, as well as the status and/orresults of one or several processing tasks could be gathered andreported to the content management server 102 from a number of sources.

Internally, the content management server 102 gathers information fromone or more internal components 402-408. The internal components 402-408gather and/or process information relating to such things as: contentprovided to users; content consumed by users; responses provided byusers; user skill levels; form reliability, content difficulty levels;next content for providing to users; etc. The internal components402-408 can report the gathered and/or generated information inreal-time, near real-time or along another time line. To account for anydelay in reporting information, a time stamp or staleness indicator caninform others of how timely the information was sampled. The contentmanagement server 102 can optionally allow third parties to useinternally or externally gathered information that is aggregated withinthe server 102 by subscription to the content distribution network 100.

A command and control (CC) interface 338 configures the gathered inputinformation to an output of data streams, also referred to herein ascontent streams. APIs for accepting gathered information and providingdata streams are provided to third parties external to the server 102who want to subscribe to data streams. The server 102 or a third partycan design as yet undefined APIs using the CC interface 338. The server102 can also define authorization and authentication parameters usingthe CC interface 338 such as authentication, authorization, login,and/or data encryption. CC information is passed to the internalcomponents 402-408 and/or other components of the content distributionnetwork 100 through a channel separate from the gathered information ordata stream in this embodiment, but other embodiments could embed CCinformation in these communication channels. The CC information allowsthrottling information reporting frequency, specifying formats forinformation and data streams, deactivation of one or several internalcomponents 402-408 and/or other components of the content distributionnetwork 100, updating authentication and authorization, etc.

The various data streams that are available can be researched andexplored through the CC interface 338. Those data stream selections fora particular subscriber, which can be one or several of the internalcomponents 402-408 and/or other components of the content distributionnetwork 100, are stored in the queue subscription information database322. The server 102 and/or the CC interface 338 then routes selecteddata streams to processing subscribers that have selected delivery of agiven data stream. Additionally, the server 102 also supports historicalqueries of the various data streams that are stored in an historicaldata store 334 as gathered by an archive data agent 336. Through the CCinterface 238 various data streams can be selected for archiving intothe historical data store 334.

Components of the content distribution network 100 outside of the server102 can also gather information that is reported to the server 102 inreal-time, near real-time or along another time line. There is a definedAPI between those components and the server 102. Each type ofinformation or variable collected by server 102 falls within a definedAPI or multiple APIs. In some cases, the CC interface 338 is used todefine additional variables to modify an API that might be of use toprocessing subscribers. The additional variables can be passed to allprocessing subscribes or just a subset. For example, a component of thecontent distribution network 100 outside of the server 102 may report auser response but define an identifier of that user as a privatevariable that would not be passed to processing subscribers lackingaccess to that user and/or authorization to receive that user data.Processing subscribers having access to that user and/or authorizationto receive that user data would receive the subscriber identifier alongwith response reported that component. Encryption and/or uniqueaddressing of data streams or sub-streams can be used to hide theprivate variables within the messaging queues.

The user devices 106 and/or supervisor devices 110 communicate with theserver 102 through security and/or integration hardware 410. Thecommunication with security and/or integration hardware 410 can beencrypted or not. For example, a socket using a TCP connection could beused. In addition to TCP, other transport layer protocols like SCTP andUDP could be used in some embodiments to intake the gatheredinformation. A protocol such as SSL could be used to protect theinformation over the TCP connection. Authentication and authorizationcan be performed to any user devices 106 and/or supervisor deviceinterfacing to the server 102. The security and/or integration hardware410 receives the information from one or several of the user devices 106and/or the supervisor devices 110 by providing the API and anyencryption, authorization, and/or authentication. In some cases, thesecurity and/or integration hardware 410 reformats or rearranges thisreceived information

The messaging bus 412, also referred to herein as a messaging queue or amessaging channel, can receive information from the internal componentsof the server 102 and/or components of the content distribution network100 outside of the server 102 and distribute the gathered information asa data stream to any processing subscribers that have requested the datastream from the messaging queue 412. Specifically, in some embodiments,the messaging bus 412 can receive and output information from at leastone of the packet selection system, the presentation system, theresponse system, and the summary model system. In some embodiments, thisinformation can be output according to a “push” model, and in someembodiments, this information can be output according to a “pull” model.

As indicated in FIG. 4, processing subscribers are indicated by aconnector to the messaging bus 412, the connector having an arrow headpointing away from the messaging bus 412. Only data streams within themessaging queue 412 that a particular processing subscriber hassubscribed to may be read by that processing subscriber if received atall. Gathered information sent to the messaging queue 412 is processedand returned in a data stream in a fraction of a second by the messagingqueue 412. Various multicasting and routing techniques can be used todistribute a data stream from the messaging queue 412 that a number ofprocessing subscribers have requested. Protocols such as Multicast ormultiple Unicast could be used to distributed streams within themessaging queue 412. Additionally, transport layer protocols like TCP,SCTP and UDP could be used in various embodiments.

Through the CC interface 338, an external or internal processingsubscriber can be assigned one or more data streams within the messagingqueue 412. A data stream is a particular type of messages in aparticular category. For example, a data stream can comprise all of thedata reported to the messaging bus 412 by a designated set ofcomponents. One or more processing subscribers could subscribe andreceive the data stream to process the information and make a decisionand/or feed the output from the processing as gathered information fedback into the messaging queue 412. Through the CC interface 338 adeveloper can search the available data streams or specify a new datastream and its API. The new data stream might be determined byprocessing a number of existing data streams with a processingsubscriber.

The CDN 110 has internal processing subscribers 402-408 that processassigned data streams to perform functions within the server 102.Internal processing subscribers 402-408 could perform functions such asproviding content to a user, receiving a response from a user,determining the correctness of the received response, updating one orseveral models based on the correctness of the response, recommendingnew content for providing to one or several users, or the like. In someembodiments, the internal processing subscriber 402-408 can receive arequest for creation of a form, receive filter inputs from the user,provide content components corresponding to the filter inputs to theuser, receive selections of content components for inclusion in theform, calculate a reliability of the form, generate recommended changesto the form, store the form, provide the form to a user, receiveresponses to the provided form, evaluate the responses, generate a scorecharacterizing the received response, updating information relevant tothe user, generating and providing an intervention or interventionrecommendation, and providing the updated information relevant to theuser.

The internal processing subscribers 402-408 can decide filtering andweighting of records from the data stream. To the extent that decisionsare made based upon analysis of the data stream, each data record istime stamped to reflect when the information was gathered such thatadditional credibility could be given to more recent results, forexample. Other embodiments may filter out records in the data streamthat are from an unreliable source or stale. For example, a particularcontributor of information may prove to have less than optimal gatheredinformation and that could be weighted very low or removed altogether.

Internal processing subscribers 402-408 may additionally process one ormore data streams to provide different information to feed back into themessaging queue 412 to be part of a different data stream. For example,hundreds of user devices 106 could provide responses that are put into adata stream on the messaging queue 412. An internal processingsubscriber 402-408 could receive the data stream and process it todetermine the difficulty of one or several data packets provided to oneor several users, and supply this information back onto the messagingqueue 412 for possible use by other internal and external processingsubscribers.

As mentioned above, the CC interface 338 allows the CDN 110 to queryhistorical messaging queue 412 information. An archive data agent 336listens to the messaging queue 412 to store data streams in a historicaldatabase 334. The historical database 334 may store data streams forvarying amounts of time and may not store all data streams. Differentdata streams may be stored for different amounts of time.

With regards to the components 402-48, the content management server(s)102 may include various server hardware and software components thatmanage the content resources within the content distribution network 100and provide interactive and adaptive content to users on various userdevices 106. For example, content management server(s) 102 may provideinstructions to and receive information from the other devices withinthe content distribution network 100, in order to manage and transmitcontent resources, user data, and server or client applicationsexecuting within the network 100.

A content management server 102 may include a packet selection system402. The packet selection system 402 may be implemented using dedicatedhardware within the content distribution network 100 (e.g., a packetselection server 402), or using designated hardware and softwareresources within a shared content management server 102. In someembodiments, the packet selection system 402 may adjust the selectionand adaptive capabilities of content resources to match the needs anddesires of the users receiving the content. For example, the packetselection system 402 may query various data stores and servers 104 toretrieve user information, such as user preferences and characteristics(e.g., from a user profile data store 301), user access restrictions tocontent recourses (e.g., from a content access data store 306), previoususer results and content evaluations (e.g., from an evaluation datastore 308), and the like. Based on the retrieved information from datastores 104 and other data sources, the packet selection system 402 maymodify content resources for individual users.

In some embodiments, the packet selection system 402 can include arecommendation engine, also referred to herein as an adaptiverecommendation engine. In some embodiments, the recommendation enginecan select one or several pieces of content, also referred to herein asdata packets or content components, for providing to a user. In someembodiments, the recommendation engine can identify one or severalcontent components for removal from a form and/or one or several contentcomponents for inclusion in a form. In some embodiments, these on orseveral content components can be identified based on their impact onthe one or several scores or statistical measures characterizing theform.

In some embodiments, for example, the reliability of a form may be toolow as compared to a threshold value. In such an embodiment, one orseveral content components in the form that are responsible fordecreasing the reliability of the form can be identified for removalfrom the form and/or can be removed from the form. Similarly, in someembodiments in which the reliability is too low, one or several contentcomponents that are not in the form can be identified for inclusion inthe form and/or can be included in the form. In some embodiments, one orseveral content components identified for inclusion in the form and/oridentified for removal from the form can be identified to the creator ofthe form for confirmation of the removal of those one or several contentcomponents from the form and/or for the confirmation of the addition ofthose one or several content components to the form.

These content components can be selected based on, for example, theinformation retrieved from the database server 104 including, forexample, the user profile database 301, the content library database303, the model database 309, or the like. In some embodiments, these oneor several data packets can be adaptively selected and/or selectedaccording to one or several selection rules, to the determinereliability of a form or draft form, or the like.

A content management server 102 also may include a summary model system404. The summary model system 404 may be implemented using dedicatedhardware within the content distribution network 100 (e.g., a summarymodel server 404), or using designated hardware and software resourceswithin a shared content management server 102. In some embodiments, thesummary model system 404 may monitor the progress of users throughvarious types of content resources and groups, such as mediacompilations, courses or curriculums in training or educationalcontexts, interactive gaming environments, and the like. For example,the summary model system 404 may query one or more databases and/or datastore servers 104 to retrieve user data such as associated contentcompilations or programs, content completion status, user goals,results, and the like. In some embodiments, the summary model system 404can generate a model, based on user response data, identifying a user'sprogress over time in developing a skill, an attribute, or the like. Insome embodiments, this can include receiving a raw score generated by,for example, the response system 406 (discussed below), and generating astandardized score from that raw score. In some embodiments, forexample, this can include the generation of a T-score from the rawscore. In some embodiments, the T-score can be a standardized score thatis positive and that has a mean of 50. In some embodiments, the T-scorecan characterize the number of standard deviations a raw score is aboveor below a mean. In some embodiments, the T-score can be used tostandardize for age, gender, or any other attribute.

A content management server 102 also may include an response system 406,which can include, in some embodiments, a response processor. Theresponse system 406 may be implemented using dedicated hardware withinthe content distribution network 100 (e.g., a response server 406), orusing designated hardware and software resources within a shared contentmanagement server 102.

The response system 406 may be configured to receive and analyzeinformation from user devices 106. For example, various ratings ofcontent resources submitted by users may be compiled and analyzed, andthen stored in a data store (e.g., a content library data store 303and/or evaluation data store 308) associated with the content. In someembodiments, the response server 406 may analyze the information todetermine the effectiveness or appropriateness of content resourceswith, for example, a subject matter, an age group, a skill level, or thelike. In some embodiments, the response system 406 may provide updatesto the packet selection system 402 or the summary model system 404, withthe attributes of one or more content resources or groups of resourceswithin the network 100.

The response system 406 also may receive and analyze user evaluationdata from user devices 106, supervisor devices 110, and administratorservers 116, etc. For instance, response system 406 may receive,aggregate, and analyze user evaluation data for different types of users(e.g., end users, supervisors, administrators, etc.) in differentcontexts (e.g., media consumer ratings, trainee or student comprehensionlevels, teacher effectiveness levels, gamer skill levels, etc.).

In some embodiments, the response system 406 can be further configuredto receive one or several responses from the user and analyze these oneor several responses. In some embodiments, for example, the responsesystem 406 can be configured to translate the one or several responsesinto one or several observables. As used herein, an observable is acharacterization of a received response. In some embodiments, thetranslation of the one or several responses into one or severalobservables can include determining whether the one or several responsesare correct responses, also referred to herein as desired responses, orare incorrect responses, also referred to herein as undesired responses.In some embodiments, the translation of the one or several responsesinto one or several observables can include characterizing the degree towhich one or several responses are desired responses and/or undesiredresponses. In some embodiments, one or several values can be generatedby the response system 406 to reflect user performance in responding tothe one or several data packets. In some embodiments, these one orseveral values can comprise one or several scores for one or severalresponses and/or data packets.

A content management server 102 also may include a presentation system408. The presentation system 408 may be implemented using dedicatedhardware within the content distribution network 100 (e.g., apresentation server 408), or using designated hardware and softwareresources within a shared content management server 102. Thepresentation system 408 can include a presentation engine that can be,for example, a software module running on the content delivery system.

The presentation system 408, also referred to herein as the presentationmodule or the presentation engine, may receive content resources fromthe packet selection system 402 and/or from the summary model system404, and provide the resources to user devices 106. The presentationsystem 408 may determine the appropriate presentation format for thecontent resources based on the user characteristics and preferences,and/or the device capabilities of user devices 106. If needed, thepresentation system 408 may convert the content resources to theappropriate presentation format and/or compress the content beforetransmission. In some embodiments, the presentation system 408 may alsodetermine the appropriate transmission media and communication protocolsfor transmission of the content resources.

In some embodiments, the presentation system 408 may include specializedsecurity and integration hardware 410, along with corresponding softwarecomponents to implement the appropriate security features contenttransmission and storage, to provide the supported network and clientaccess models, and to support the performance and scalabilityrequirements of the network 100. The security and integration layer 410may include some or all of the security and integration components 208discussed above in FIG. 2, and may control the transmission of contentresources and other data, as well as the receipt of requests and contentinteractions, to and from the user devices 106, supervisor devices 110,administrative servers 116, and other devices in the network 100.

With reference now to FIG. 5, a block diagram of an illustrativecomputer system is shown. The system 500 may correspond to any of thecomputing devices or servers of the content distribution network 100described above, or any other computing devices described herein, andspecifically can include, for example, one or several of the userdevices 106, the supervisor device 110, and/or any of the servers 102,104, 108, 112, 114, 116. In this example, computer system 500 includesprocessing units 504 that communicate with a number of peripheralsubsystems via a bus subsystem 502. These peripheral subsystems include,for example, a storage subsystem 510, an I/O subsystem 526, and acommunications subsystem 532.

Bus subsystem 502 provides a mechanism for letting the variouscomponents and subsystems of computer system 500 communicate with eachother as intended. Although bus subsystem 502 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 502 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Sucharchitectures may include, for example, an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard.

Processing unit 504, which may be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 500. One or more processors,including single core and/or multicore processors, may be included inprocessing unit 504. As shown in the figure, processing unit 504 may beimplemented as one or more independent processing units 506 and/or 508with single or multicore processors and processor caches included ineach processing unit. In other embodiments, processing unit 504 may alsobe implemented as a quad-core processing unit or larger multicoredesigns (e.g., hexa-core processors, octo-core processors, ten-coreprocessors, or greater.

Processing unit 504 may execute a variety of software processes embodiedin program code, and may maintain multiple concurrently executingprograms or processes. At any given time, some or all of the programcode to be executed can be resident in processor(s) 504 and/or instorage subsystem 510. In some embodiments, computer system 500 mayinclude one or more specialized processors, such as digital signalprocessors (DSPs), outboard processors, graphics processors,application-specific processors, and/or the like.

I/O subsystem 526 may include device controllers 528 for one or moreuser interface input devices and/or user interface output devices 530.User interface input and output devices 530 may be integral with thecomputer system 500 (e.g., integrated audio/video systems, and/ortouchscreen displays), or may be separate peripheral devices which areattachable/detachable from the computer system 500. The I/O subsystem526 may provide one or several outputs to a user by converting one orseveral electrical signals to user perceptible and/or interpretableform, and may receive one or several inputs from the user by generatingone or several electrical signals based on one or several user-causedinteractions with the I/O subsystem such as the depressing of a key orbutton, the moving of a mouse, the interaction with a touchscreen ortrackpad, the interaction of a sound wave with a microphone, or thelike.

Input devices 530 may include a keyboard, pointing devices such as amouse or trackball, a touchpad or touch screen incorporated into adisplay, a scroll wheel, a click wheel, a dial, a button, a switch, akeypad, audio input devices with voice command recognition systems,microphones, and other types of input devices. Input devices 530 mayalso include three dimensional (3D) mice, joysticks or pointing sticks,gamepads and graphic tablets, and audio/visual devices such as speakers,digital cameras, digital camcorders, portable media players, webcams,image scanners, fingerprint scanners, barcode reader 3D scanners, 3Dprinters, laser rangefinders, and eye gaze tracking devices. Additionalinput devices 530 may include, for example, motion sensing and/orgesture recognition devices that enable users to control and interactwith an input device through a natural user interface using gestures andspoken commands, eye gesture recognition devices that detect eyeactivity from users and transform the eye gestures as input into aninput device, voice recognition sensing devices that enable users tointeract with voice recognition systems through voice commands, medicalimaging input devices, MIDI keyboards, digital musical instruments, andthe like.

Output devices 530 may include one or more display subsystems, indicatorlights, or non-visual displays such as audio output devices, etc.Display subsystems may include, for example, cathode ray tube (CRT)displays, flat-panel devices, such as those using a liquid crystaldisplay (LCD) or plasma display, light-emitting diode (LED) displays,projection devices, touch screens, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system500 to a user or other computer. For example, output devices 530 mayinclude, without limitation, a variety of display devices that visuallyconvey text, graphics and audio/video information such as monitors,printers, speakers, headphones, automotive navigation systems, plotters,voice output devices, and modems.

Computer system 500 may comprise one or more storage subsystems 510,comprising hardware and software components used for storing data andprogram instructions, such as system memory 518 and computer-readablestorage media 516. The system memory 518 and/or computer-readablestorage media 516 may store program instructions that are loadable andexecutable on processing units 504, as well as data generated during theexecution of these programs.

Depending on the configuration and type of computer system 500, systemmemory 318 may be stored in volatile memory (such as random accessmemory (RAM) 512) and/or in non-volatile storage drives 514 (such asread-only memory (ROM), flash memory, etc.) The RAM 512 may contain dataand/or program modules that are immediately accessible to and/orpresently being operated and executed by processing units 504. In someimplementations, system memory 518 may include multiple different typesof memory, such as static random access memory (SRAM) or dynamic randomaccess memory (DRAM). In some implementations, a basic input/outputsystem (BIOS), containing the basic routines that help to transferinformation between elements within computer system 500, such as duringstart-up, may typically be stored in the non-volatile storage drives514. By way of example, and not limitation, system memory 518 mayinclude application programs 520, such as client applications, Webbrowsers, mid-tier applications, server applications, etc., program data522, and an operating system 524.

Storage subsystem 510 also may provide one or more tangiblecomputer-readable storage media 516 for storing the basic programmingand data constructs that provide the functionality of some embodiments.Software (programs, code modules, instructions) that when executed by aprocessor provide the functionality described herein may be stored instorage subsystem 510. These software modules or instructions may beexecuted by processing units 504. Storage subsystem 510 may also providea repository for storing data used in accordance with the presentinvention.

Storage subsystem 300 may also include a computer-readable storage mediareader that can further be connected to computer-readable storage media516. Together and, optionally, in combination with system memory 518,computer-readable storage media 516 may comprehensively representremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containing, storing,transmitting, and retrieving computer-readable information.

Computer-readable storage media 516 containing program code, or portionsof program code, may include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible computer-readable storagemedia such as RAM, ROM, electronically erasable programmable ROM(EEPROM), flash memory or other memory technology, CD-ROM, digitalversatile disk (DVD), or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or other tangible computer readable media. This can also includenontangible computer-readable media, such as data signals, datatransmissions, or any other medium which can be used to transmit thedesired information and which can be accessed by computer system 500.

By way of example, computer-readable storage media 516 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 516 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 516 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 500.

Communications subsystem 532 may provide a communication interface fromcomputer system 500 and external computing devices via one or morecommunication networks, including local area networks (LANs), wide areanetworks (WANs) (e.g., the Internet), and various wirelesstelecommunications networks. As illustrated in FIG. 5, thecommunications subsystem 532 may include, for example, one or morenetwork interface controllers (NICs) 534, such as Ethernet cards,Asynchronous Transfer Mode NICs, Token Ring NICs, and the like, as wellas one or more wireless communications interfaces 536, such as wirelessnetwork interface controllers (WNICs), wireless network adapters, andthe like. As illustrated in FIG. 5, the communications subsystem 532 mayinclude, for example, one or more location determining features 538 suchas one or several navigation system features and/or receivers, and thelike. Additionally and/or alternatively, the communications subsystem532 may include one or more modems (telephone, satellite, cable, ISDN),synchronous or asynchronous digital subscriber line (DSL) units,FireWire® interfaces, USB® interfaces, and the like. Communicationssubsystem 536 also may include radio frequency (RF) transceivercomponents for accessing wireless voice and/or data networks (e.g.,using cellular telephone technology, advanced data network technology,such as 3G, 4G or EDGE (enhanced data rates for global evolution), WiFi(IEEE 802.11 family standards, or other mobile communicationtechnologies, or any combination thereof), global positioning system(GPS) receiver components, and/or other components.

The various physical components of the communications subsystem 532 maybe detachable components coupled to the computer system 500 via acomputer network, a FireWire® bus, or the like, and/or may be physicallyintegrated onto a motherboard of the computer system 500. Communicationssubsystem 532 also may be implemented in whole or in part by software.

In some embodiments, communications subsystem 532 may also receive inputcommunication in the form of structured and/or unstructured data feeds,event streams, event updates, and the like, on behalf of one or moreusers who may use or access computer system 500. For example,communications subsystem 532 may be configured to receive data feeds inreal-time from users of social networks and/or other communicationservices, web feeds such as Rich Site Summary (RSS) feeds, and/orreal-time updates from one or more third party information sources(e.g., data aggregators 311). Additionally, communications subsystem 532may be configured to receive data in the form of continuous datastreams, which may include event streams of real-time events and/orevent updates (e.g., sensor data applications, financial tickers,network performance measuring tools, clickstream analysis tools,automobile traffic monitoring, etc.). Communications subsystem 532 mayoutput such structured and/or unstructured data feeds, event streams,event updates, and the like to one or more data stores 104 that may bein communication with one or more streaming data source computerscoupled to computer system 500.

Due to the ever-changing nature of computers and networks, thedescription of computer system 500 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software, or acombination. Further, connection to other computing devices, such asnetwork input/output devices, may be employed. Based on the disclosureand teachings provided herein, a person of ordinary skill in the artwill appreciate other ways and/or methods to implement the variousembodiments.

With reference now to FIG. 6, a block diagram illustrating oneembodiment of the communication network is shown. Specifically, FIG. 6depicts one hardware configuration in which messages are exchangedbetween a source hub 602 via the communication network 120 that caninclude one or several intermediate hubs 604. In some embodiments, thesource hub 602 can be any one or several components of the contentdistribution network generating and initiating the sending of a message,and the terminal hub 606 can be any one or several components of thecontent distribution network 100 receiving and not re-sending themessage. In some embodiments, for example, the source hub 602 can be oneor several of the user device 106, the supervisor device 110, and/or theserver 102, and the terminal hub 606 can likewise be one or several ofthe user device 106, the supervisor device 110, and/or the server 102.In some embodiments, the intermediate hubs 604 can include any computingdevice that receives the message and resends the message to a next node.

As seen in FIG. 6, in some embodiments, each of the hubs 602, 604, 606can be communicatingly connected with the data store 104. In such anembodiments, some or all of the hubs 602, 604, 606 can send informationto the data store 104 identifying a received message and/or any sent orresent message. This information can, in some embodiments, be used todetermine the completeness of any sent and/or received messages and/orto verify the accuracy and completeness of any message received by theterminal hub 606.

In some embodiments, the communication network 120 can be formed by theintermediate hubs 604. In some embodiments, the communication network120 can comprise a single intermediate hub 604, and in some embodiments,the communication network 120 can comprise a plurality of intermediatehubs. In one embodiment, for example, and as depicted in FIG. 6, thecommunication network 120 includes a first intermediate hub 604-A and asecond intermediate hub 604-B.

With reference now to FIG. 7, a block diagram illustrating oneembodiment of user device 106 and supervisor device 110 communication isshown. In some embodiments, for example, a user may have multipledevices that can connect with the content distribution network 100 tosend or receive information. In some embodiments, for example, a usermay have a personal device such as a mobile device, a Smartphone, atablet, a Smartwatch, a laptop, a PC, or the like. In some embodiments,the other device can be any computing device in addition to the personaldevice. This other device can include, for example, a laptop, a PC, aSmartphone, a tablet, a Smartwatch, or the like. In some embodiments,the other device differs from the personal device in that the personaldevice is registered as such within the content distribution network 100and the other device is not registered as a personal device within thecontent distribution network 100.

Specifically with respect to FIG. 7, the user device 106 can include apersonal user device 106-A and one or several other user devices 106-B.In some embodiments, one or both of the personal user device 106-A andthe one or several other user devices 106-B can be communicatinglyconnected to the content management server 102 and/or to the navigationsystem 122. Similarly, the supervisor device 110 can include a personalsupervisor device 110-A and one or several other supervisor devices110-B. In some embodiments, one or both of the personal supervisordevice 110-A and the one or several other supervisor devices 110-B canbe communicatingly connected to the content management server 102 and/orto the navigation system 122.

In some embodiments, the content distribution network can send one ormore alerts to one or more user devices 106 and/or one or moresupervisor devices 110 via, for example, the communication network 120.In some embodiments, the receipt of the alert can result in thelaunching of an application within the receiving device, and in someembodiments, the alert can include a link that, when selected, launchesthe application or navigates a web-browser of the device of the selectorof the link to page or portal associated with the alert. In someembodiments, the prompt can comprise an alert configured to triggeractivation of the I/O subsystem of a user device 106 of a follow-upuser, also referred to herein as a second user device, to provide anotification of the exceeded threshold

In some embodiments, for example, the providing of this alert caninclude the identification of one or several user devices 106 and/orstudent-user accounts associated with the student-user and/or one orseveral supervisor devices 110 and/or supervisor-user accountsassociated with the supervisor-user. After these one or several devices106, 110 and/or accounts have been identified, the providing of thisalert can include determining an active device of the devices 106, 110based on determining which of the devices 106, 110 and/or accounts areactively being used, and then providing the alert to that active device.

Specifically, if the user is actively using one of the devices 106, 110such as the other user device 106-B and the other supervisor device110-B, and/or accounts, the alert can be provided to the user via thatother device 106-B, 110-B and/or account that is actively being used. Ifthe user is not actively using an other device 106-B, 110-B and/oraccount, a personal device 106-A, 110-A device, such as a smart phone ortablet, can be identified and the alert can be provided to this personaldevice 106-A, 110-A. In some embodiments, the alert can include code todirect the default device to provide an indicator of the received alertsuch as, for example, an aural, tactile, or visual indicator of receiptof the alert.

In some embodiments, the recipient device 106, 110 of the alert canprovide an indication of receipt of the alert. In some embodiments, thepresentation of the alert can include the control of the I/O subsystem526 to, for example, provide an aural, tactile, and/or visual indicatorof the alert and/or of the receipt of the alert. In some embodiments,this can include controlling a screen of the supervisor device 110 todisplay the alert, data contained in alert and/or an indicator of thealert.

With reference now to FIG. 8, a schematic illustration of one embodimentof an automatic content remediation notification system 490 is shown.The automatic content remediation notification system 490 can comprisesome or all of the components of the content distribution network 100including, for example, one or several servers 102, the data storeserver 104, one or several user devices 106, one or several supervisordevices 110, and/or the communication network 120. In some embodiments,the user devices 106 and/or supervisor devices 110 can be one or severalclient computing devices 206 as indicated in FIG. 8.

In some embodiments, the automatic content remediation notificationsystem 490 can further include one or several modules that can beembodied in hardware or software, including, for example, an interfacemodule 492, an administrator module 494, a design interface module 496,the response processor 678, and/or the database server 104. In someembodiments, some or all of the interface module 492, the administratormodule 494, the design interface module 496, and the response processor678 can be one or several hardware modules separate from the one orseveral servers 102 and/or one or several software modules that can beimplemented on the one or several servers 102 or on other hardware.

The automatic content remediation notification system 490 can, in someembodiments, be used by the user of the supervisor device 110 to createand/or author content such as one or several data packets, to create oneor several content aggregates which can each comprise one or severaldata packets, to assign one or several content aggregates to a user,which user is referred to herein as the assigned user or the recipientuser, to provide the one or several data packets to the assigned user,and to receive any responses from the assigned user. In someembodiments, some or all of the content aggregations can be evaluationssuch as, for example, psychometric evaluations. In some embodiments,these evaluations can evaluate one or several psychological states orproblems, one or several behavior types, or the like.

In some embodiments, the automatic content remediation notificationsystem 490 can be further configured to automatically generate a contentscore for a created content aggregation. In some embodiments, thecontent score can comprise a reliability value that can indicate thereliability of any outcome generated in response to a user's completionof the content aggregation, and that can specifically identify theexpected overall consistency of the content aggregation in repeatedlygenerating the same results under the same conditions. In someembodiments, the reliability value can be based on metadata of the datapackets forming the content aggregate. This reliability value can be, insome embodiments, Cronbach's α, and, in some embodiments, thisreliability value can be generate for an age group of the recipient userand/or for several age groups. Thus, in some embodiments, a firstreliability of a content aggregation can be calculated for a first agegroup, a second reliability of the content aggregation can be calculatedfor a second age group, a third reliability of the content aggregationcan be calculated for a third age group, etc.

In some embodiments, the automatic content remediation notificationsystem 490 can be further configured to identify a norm group based onthe recipient user. The norm group can be a group of a plurality ofsimilar users who have already completed the content aggregations and/orsome or all of the data packets associated with the content aggregation.In some embodiments, the norm group can include norm data previouslygathered from the plurality of similar users to the intended recipient.

In some embodiments, the norm group and/or the norm data can be used ingenerating one or several additional statistical parameters, alsoreferred to herein as supplemental statistical parameters that can beused in evaluating the one or several responses to the contentaggregation. These additional statistical parameters can be calculatedfrom the norm data and can include, for example, a mean, a median, amode, a deviation measure, and/or a standard deviation.

In some embodiments, the automatic content remediation notificationsystem 490 can be further configured to track the amount of time elapsedsince the sending of one or several content aggregations to a user andto compare the lapsed time to one or several thresholds to determinewhether to provide a remediation and/or prompt to the assigned userand/or to a follow-up user. As used herein a follow-up user is the userassociated with the recipient user but who is not the recipient user. Insome embodiments, the follow-up user can have some responsibilityvis-à-vis the recipient user for completion of one or several activitiesassociated with one or several data packets. The follow-up user caninclude, for example, a parent, guardian, tutor, assistant, trainer,facilitator, or the like.

In some embodiments, the automatic content remediation notificationsystem 490 can be configured to automatically generate and send a promptto at least the follow-up user when the lapsed time exceeds one orseveral thresholds. In some embodiments, this prompt can comprise analert the receipt of which alert can result in the launching of anapplication within the receiving device, and in some embodiments, thealert can include a link that, when selected, launches the applicationor navigates a web-browser of the device of the selector of the link topage or portal associated with the alert. In some embodiments, thisalert can comprise data relating to the provided data packet and/oractivity, the amount of lapsed time since receipt of the data packetand/or activity, reward information, the medial information, or thelike.

In some embodiments, the automatic content remediation notificationsystem 490 can be configured to receive a response to the providedcontent aggregation and evaluate the response. In some embodiments, andas a result of the evaluation, the automatic content remediationnotification system 490 can be configured to update user data relatingto the recipient user and/or generate a provide a report based on theupdated user data. In some embodiments, and as a result of theevaluation, the automatic content remediation notification system 490can be configured to generate a remediation, which remediation can beautomatically generated and/or delivered to the recipient user, thefollow-up user, and/or the user of the supervisor device 110. In someembodiments, the remediation can comprise an alert that can be generatedand sent to the recipient user, the follow-up user, and/or the user ofthe supervisor device 110 via the communications network 120. In someembodiments, the alert can include a link that, when selected, launchesthe application or navigates a web-browser of the device of the selectorof the link to page or portal associated with the alert.

The interface module 492 can be configured to interact with the userdevice 106 and/or the supervisor device 110 to deliver one or severalcontent aggregations to the user and/or to facilitate in the creation ofone or several content aggregations. In some embodiments, the interfacemodule 492 can be configured to generate and/or control one or severaluser interfaces on the user device and/or the supervisor device 110.

In some embodiments, the administrator module 494 can be configured tosend information and/or signals to, and receive information and/orsignals from the other components of the automatic content remediationnotification system 490. In some embodiments, the administrator modulecan coordinate the operation of other components of the automaticcontent remediation notification system 490 and/or control communicationbetween the other components of the automatic content remediationnotification system 490.

The administrator module 494 can communicate and/or direct communicationwith the supervisor device 110 for the creation of content and/or datapackets which can then be stored in the database server 104. Theadministrator module 494 can further communicate and/or directcommunication with the supervisor device 110 for the generation and/orselection of a content aggregation for providing to the recipient uservia a user device 106 associated and/or owned or controlled by therecipient user. The administrator module 494 can then send the selectedcontent aggregation to the user device 106 of the recipient user via thecommunication network 120.

The administrator module 494 can trigger a timer to measure lapsed timesince the sending of the content aggregation to the recipient user. Theadministrator module can further compare the timer to one or severalthresholds to determine whether to generate and/or send a remediationand/or prompt to the recipient user, the follow-up user, and/or the userthe supervisor device 110. If the administrator module 494 determines togenerate and/or send a prompt and/or remediation, the administratormodule 494 can direct the sending of such a prompt and/or remediation.This prompt and/or remediation can be sent via a notification systemand/or service such as, for example, Apple Push Notification Service,Amazon Simple Notification Service, Android Cloud to Device Messaging,Google Cloud Messaging, or the like. In some embodiments, thisnotification can be a push notification.

The administrator module 494 can receive a response from recipient uservia the user device 106, which response can be to the contentaggregation provided to the recipient user. The administrator module 494can provide the response to the response processor 678 which canevaluate the response to determine whether the response is correct orincorrect and/or the degree to which the response is correct orincorrect. In some embodiments, the data packet can comprise an activityrelating to speech therapy, also referred to herein as oral training, inthe response can comprise, for example, a video and/or audio file of therecipient user performing the activity. In some embodiments, this caninclude video and/or audio file of the recipient user saying one orseveral letters, sounds, words, or the like. In some embodiments, theresponse processor 678 can compare the response to a model response thatcan be received from the content library database 303 in the databaseserver 104.

The response processor 678 can generate a report indicating the resultof the evaluation of the received response and can provide this reportto the administrator module 494. In some embodiments, this report canidentify the outcome of the evaluation of the received response and/orprovide tracking of any progress made by the user over time with respectto one or several traits, behaviors, or the like. Based on the receivedreport, the administrator module 494 can determine whether remediationis desired, and can provide a remediation when the remediation isdesired.

The automatic content remediation notification system 490 can include adesign interface module 496. The design interface module 496 can be incommunication with one or several supervisor devices 110 which can beone or several client computing devices 206 as indicated in FIG. 8. Insome embodiments, the user of the supervisor device 100 can interactwith the design interface module 494 to create one or several contentaggregations. In some embodiments, the design interface module canfurther communicate with the packet selection system 402 to facilitatein the recommendation of one or several content components for inclusionin the content aggregation and/or the recommendation of one or severalcontent components for removal from the content aggregation.

With reference now to FIG. 9, a swim lane diagram of one embodiment of aprocess 700 for content aggregation creation is shown. The process 700can be performed by all or portions of the content distribution network100 and specifically by all or portions of the automatic contentremediation notification system 490. The process 700 begins at block702, wherein a creation input is received by the supervisor device 110from the user of the supervisor device 110 via the I/O subsystem 526 ofthe supervisor device 100. In some embodiments the creation request caninclude data identifying the user of the supervisor device 110,identifying the intended recipient of the content aggregation, or thelike.

In some embodiments, the creation input can be received via a managementinterface 850 as shown in FIG. 10. The management interface can includea display panel 852 that display information relating to existing formsincluding, for example, a form name, a form status, an identifier of theform creator, whether the form is shared, and the date the form iscreated. The management interface 850 further includes a creation button854. In some embodiments, activation of the creation button 854 canresult in the receipt of the creation input by the supervisor device110.

After the creation input has been received, the process 700 proceeds toblock 704, wherein a creation request is generated and/or sent by thesupervisor device 110. In some embodiments, the creation requestcomprises a communication, and specifically an electrical communicationcontaining data identifying a request for content aggregation creation.In some embodiments, the creation request can be generated and/or sentas a consequence of the receipt of the creation input. In someembodiments, the supervisor device 110 can generate this request and cansend this request to the interface module 492 and/or the designinterface module 494 via the communication network 120. After thecreation request has been generated and sent, the process 700 proceedsto block 706, wherein the creation request is received by the interfacemodule 492 and/or by the design interface module 494. The receipt of thecreation request can result in the automatic triggering of the launchingof an application, such as a form application, through which the contentaggregation can be created. In some embodiments, the form applicationcan provide one or several software tools and/or capabilities tofacilitate the creation of the content aggregation. The form applicationcan be a software module that can be located on the interface module494, the administrator module 494, and/or the design interface module494.

In some embodiments, the launching of the form application can includethe generating and sending of one or several signals to the supervisordevice 110 directing the supervisor device 110 to, as indicated in block710 of FIG. 7, launch a user interface, also referred to herein as aform builder user interface (U/I) which can facilitate the creation ofthe content aggregation. The receipt of these one or several signals canresult in the launching of the form builder user interface by thesupervisor device 110, and specifically by the I/O subsystem 526.

One embodiment of the form builder user interface 860 is shown in FIG.11. The form builder user interface 860 can include a filter panel 862.In some embodiments, the filter panel 862 can include one or severalfeatures that are manipulable to provide one or several filter inputs.In some embodiments, these filter inputs can identify a rater, one orseveral age groups, a test category or test type, or the like. The formbuilder user interface 860 can include a content component displaywindow 864, also referred to herein as an item bank window 864 or itembank 864. In some embodiments, the content component display window 864can display one or several content components that match the filterinputs. In some embodiments, the display of one or several of thecontent components can include the display of unique information foreach of the displayed content components. This information can include,for example, a name or subject of the content component.

The form builder user interface 860 can include a custom form window866, also referred to herein as a custom form display 866. The customform display 866 can identify content components for inclusion in theform that is being created. In some embodiments, the custom form displaycan comprise a window in which the user may drag-and-drop contentcomponents selected and/or dragged from the item bank window 864. FIG.12 shows one embodiment of the form builder user interface 860 wherein acontent components 867 have already been added to the form and are thusdisplayed in the custom form display 866, and wherein a contentcomponent 869 is being dragged to the custom form display 866 for addingto the form. In some embodiments, the form builder user interface 860can track the number of content components in the custom form displayand can indicate this number to the user. In some embodiments, arecommended number of content components can be displayed, for example,next to the custom form display 866. In some embodiments, for example, acustom form can include between 5 and 45 content components.

After the launch of the user interface, the process 700 proceeds toblock 712 wherein filter inputs are received. In some embodiments, thefilter inputs can be received via the one or several features of thefilter panel 862. The filter components can specify one or severalparameters that can be used to select data packets for potentialinclusion in the content aggregation. In some embodiments these filterinputs can, for example, specify a difficulty level, a content,relevance to a topic, content, relevance to a behavior, or the like. Insome embodiments, these filter inputs can specify one or severalattributes relevant to the intended recipient such as an age, gender,race, ethnicity, language, education level, or the like. The filterinputs can be received by the supervisor device 110 via the I/Osubsystem 526 of the supervisor device 110.

After the filter inputs have been received, the process 700 proceeds toblock 714, wherein filter requests are generated and/or sent. In someembodiments, the filter requests can comprise one or several electricalsignals that can be generated by the supervisor device 110 based on thereceived filter inputs. The filter requests can be sent by thesupervisor device 110 to the one or several servers 102, andspecifically to the interface module 492 and/or the design interfacemodule 496. The filter requests can be received by the interface module492 and/or the design interface module 496 as indicated in block 716 ofprocess 700, and the relevant content can then be retrieved and/oridentified based on the received filter requests. In some embodiments,the relevant content can comprise one or several data packets complyingwith the filter requests. In some embodiments, the retrieving therelevant data packets can include querying the database server 104, andspecifically the content library database 303 for data packets meetingthe requirements of the filter requests. In some embodiments, this caninclude filtering the data packets in the content library database 303.

After the relevant data packets have been retrieved, the process 700proceeds to block 722, wherein one or several potential acceptablecombinations are identified. In some embodiments, this can includeidentifying one or several combinations of the relevant data packetsthat can be combined into a packet aggregation and that would meetreliability requirements and/or standards. In some embodiments, this caninclude the identification of one or several potential groupings ofcontent, the automatic generation of a reliability coefficient, alsoreferred to herein as a reliability score, for each of these potentialgroupings, the comparison of these reliability coefficients to athreshold value, and the identification of a potential grouping asacceptable when the reliability coefficient for that potential groupingexceeds the threshold value. In some embodiments, the identification ofpotential acceptable combinations can be performed by the responseprocessor 678.

After the potential acceptable combinations have been identified, theprocess 700 proceeds to block 724, wherein the filtered content, or inother words, wherein the relevant content is provided. In someembodiments, this can include the providing of the data packets to thesupervisor device 110 via the communication network 120 and in someembodiments, this can include the providing of data relating to therelevant data packets to the supervisor device via the communicationnetwork 120.

The filtered content is received by the supervisor device, and contentselections can be received by the supervisor device 110 as indicated inblock 726 of FIG. 9. Specifically, in some embodiments, the filteredcontent can be received and can be provided to the user of thesupervisor device 110 via, for example, the component display window864. In some embodiments, the content selection can include the receiptof one or several inputs from the user identifying one or several datapackets from the set of filtered content for inclusion in a contentaggregation. In some embodiments, this can include the dragging anddropping of one or several content components from the component displaywindow 864 to the custom form display 866. In some embodiments, theseselections can be received by the supervisor device 110 via the I/Osubsystem 526 of the supervisor device 110.

After the content selections have been received, the process 700proceeds to block 728, wherein a content aggregation is generated and/orsent. In some embodiments, the generation of the content aggregation caninclude the grouping of the selected data packets into the contentaggregation. In some embodiments, the content aggregation can begenerated by the supervisor device 110. In some embodiments, the contentaggregation and/or data indicating the selected data packets can be sentfrom the supervisor device to the one or several servers 102 and/or tothe interface module 492 and/or the design interface module 496. Thecontent aggregation and/or the data identifying the selected datapackets can be received by the interface module 492 and/or the designinterface module 496 as indicated in block 730, and the contentaggregation and/or the data packets forming the content aggregation canbe provided to the response processor 678 for evaluation. In someembodiments, the generating and sending of the content aggregation canbe performed in response to user manipulation of a scoring button 870located in the form builder user interface 860 as shown in FIG. 13.

The content aggregation can be evaluated by the response processor 678as indicated in block 732 of FIG. 9. In some embodiments, this caninclude the generation of one or several reliability coefficients forthe content aggregation. These one or several reliability coefficientscan be generated from metadata associated with the one or several datapackets forming the content aggregation. This reliability coefficientcan be, in some embodiments, Cronbach's α, and, in some embodiments,this reliability value can be generated for an age group of therecipient user and/or for several age groups. In some embodiments, thereliability coefficient can be sent to the supervisor device 110 and canbe displayed to the user of the supervisor device 110 as a part of theform builder user interface 860. In some embodiments, the reliabilitycoefficient can comprise a plurality of reliabilities that can be, forexample, based on one or several attributes of the intended recipient ofthe form such as, for example, the age of the intended recipient of theform. In some embodiments, these reliabilities scores can be displayedin a reliability window 872 shown in FIG. 13.

After the content aggregation has been evaluated, the process 700proceeds to decision state 734, wherein the reliability coefficient iscompared to a threshold. In some embodiments, the threshold candelineate between acceptable reliability coefficients and unacceptablereliability coefficients. The threshold can be retrieved from thedatabase server 104 and specifically from the threshold database 310.The response processor 678 can compare the reliability coefficient tothe threshold to determine if the reliability coefficient is acceptableor unacceptable.

If it is determined that the reliability coefficient is acceptable, thenthe process 700 proceeds to block 736, wherein the content aggregationis stored. In some embodiments, the content aggregation can be storedvia user interaction with the form builder user interface 860, andspecifically with one or several save features 874 of the form builderuser interface 860 as shown in FIG. 13. In some embodiments, forexample, the save features 874 can comprise one or several save buttons,the manipulation of which can result in the storage of the contentaggregation.

In some embodiments, the storing of the content aggregation can beperformed in response to the receipt of a save request received via savecontrols located in the form builder user interface 860. In someembodiments, the content aggregation can be named via a user input in aname window 876, and the content aggregation can be stored in thedatabase server 104, and specifically within the content librarydatabase 303 of the database server 104.

Returning again to decision state 734, if it is determined that thereliability coefficient is unacceptable, then the process 700 proceedsto block 738, wherein a compliance recommendation is generated and/orprovided. In some embodiments, the compliance recommendation cancomprise a recommendation for a change to the content aggregation. Insome embodiments, this change can include the addition of one or severaldata packets to the content aggregation, the removal of one or severalpackets from the content aggregation, or the like. In some embodiments,the compliance recommendation can comprise a proposed change to thecontent aggregation, which change would result in an increase in thereliability coefficient and/or the meeting and/or exceeding of thethreshold by the reliability coefficient when the content aggregation ismodified according to the compliance recommendation. In someembodiments, the compliance recommendation can be generated by theresponse processor 678, the form application, and/or any other componentor module of the content distribution network 100. The compliancerecommendation can be provided to the supervisor device 110 by the formapplication, the interface module 492 and/or the design interface module496.

After the compliance recommendation has been generated, the compliancerecommendation can be provided to the supervisor device 110. In someembodiments, the compliance recommendation can be provided to thesupervisor device 110 in the form of an alert that can be generated andsent to the supervisor device 110 via the communications network 120. Insome embodiments, the alert can include a link that, when selected,launches the application or navigates a web-browser of the device of theselector of the link to page or portal associated with the alert. Afterthe compliance recommendation has been generated and sent, the process700 continues to block 726 and continues as outlined above.

With reference now to FIG. 14, a flowchart illustrating one embodimentof a process 750 for content aggregation creation is shown. The process750 can be performed by all or portions of the content distributionnetwork 100 and specifically by all or portions of the automatic contentremediation notification system 490. The process 750 begins at block752, wherein a content creation request is received. In someembodiments, the content creation request can be received by theinterface module 492 and/or by the design interface module 494 from thesupervisor device 110. The receipt of the creation request can result inthe automatic triggering of the launching of an application, such as aform application, through which the content aggregation can be created.In some embodiments, the form application can provide one or severalsoftware tools and/or capabilities to facilitate the creation of thecontent aggregation. The form application can be a software module thatcan be located on the interface module 494, the administrator module494, and/or the design interface module 494.

After the content creation request has been received, the process 750proceeds to block 756, wherein one or several signals directing thesupervisor device 110 to launch a user interface, also referred toherein as a form builder user interface (U/I), are generated and/orsent. In some embodiments, this trigger signal to cause the supervisordevice 110 to launch the local interface can be generated and send bythe one or several servers 102, and specifically by the interface module492 and/or by the design interface module 494.

After the local interface launch has been triggered, the process 750proceeds to block 758, wherein filter requests are received. In someembodiments, the filter requests can be received by the interface module492 and/or the design interface module 496. In some embodiments, thesefilter requests can be received subsequent to the user providing of oneor several filter inputs to the supervisor device 110.

After the filter requests have been received, the process 750 canproceed to block 760, wherein relevant content is filtered, retrieved,and/or identified. In some embodiments, relevant content can befiltered, retrieved, and/or identified based on the received filterrequests. The relevant content can comprise one or several data packetscomplying with the filter requests.

Retrieving the relevant data packets can, in some embodiments, includequerying the database server 104, and specifically the content librarydatabase 303 for data packets meeting the requirements of the filterrequests. In some embodiments, this can include filtering the datapackets in and/or received from the content library database 303.

After the relevant content has been filtered, retrieved, and/oridentified, the process 750 proceeds to block 762, wherein one orseveral potential groupings are identified. In some embodiments, thiscan include identifying one or several combinations of the relevant datapackets that can be combined into a packet aggregation and that wouldmeet reliability requirements and/or standards. In some embodiments,this can include the identification of one or several potentialgroupings of content, the automatic generation of a reliabilitycoefficient for each of these potential groupings, the comparison ofthese reliability coefficients to a threshold value, and theidentification of a potential grouping as acceptable when thereliability coefficient for that potential grouping exceeds thethreshold value. In some embodiments, the identification of potentialacceptable combinations can be performed by the response processor 678.In some embodiments, these potential groupings can be identified basedin part on the received filter inputs. Specifically, in someembodiments, these potential grouping can be generated for topics,content, behaviors, or the like specified in received filter inputs. Insome embodiments, these potential groupings can be provided to the uservia the supervisor device 110, and the user can select one or several ofthese potential groupings for formation of the content aggregation. Ifsuch a grouping is selected, and if no additional content components areadded to the content aggregation, then the process 750 can proceed toblock 776 as discussed below.

After the potential groupings have been identified, the process 750proceeds to block 764, wherein the filtered content is provided. In someembodiments, the filtered content can be provided to the supervisordevice 110 by the one or several servers 102, the interface module 492and/or the design interface module 496. In some embodiments, this caninclude the providing of the data packets to the supervisor device 110via the communication network 120 and in some embodiments, this caninclude the providing of data relating to the relevant data packets tothe supervisor device via the communication network 120.

After the filtered content has been provided, the process 750 proceedsto block 766, wherein the content aggregation and/or informationidentifying the data packets forming the content aggregation isreceived. In some embodiments, the content aggregation and/or theinformation identifying the data packets forming the content aggregationcan be received by the one or several servers 102, the interface module492 and/or the design interface module 496.

After the content aggregation has been received, the process 750proceeds to block 770, wherein the content aggregation is evaluated. Insome embodiments, this can include the generation of one or severalcontent scores that can include, for example, one or several reliabilitycoefficients for the content aggregation and/or one or several scoresindicative of comprehensiveness of the content aggregation. In someembodiments, the reliability coefficient can characterize the expectedrepeatability of results generated by the content aggregation. This caninclude the expected repeatability of results generated by the contentaggregation under the same or similar circumstances. A comprehensivenessscore can identify the degree to which the content aggregation includescontent components addressing all or portions of the topics, content,behaviors, or the like specified in received filter inputs.

The one or several reliability coefficients can be generated frommetadata associated with the one or several data packets forming thecontent aggregation. This reliability coefficient can be, in someembodiments, Cronbach's α, and, in some embodiments, this reliabilityvalue can be generate for an age group of the recipient user and/or forseveral age groups.

In some embodiments, for example, the generation of one or severalreliability coefficients comprises: identifying the content componentsforming the content aggregation; retrieving data associated with thecontent components of the content aggregation; inputting the retrieveddata into a reliability algorithm and/or equation; and outputting areliability coefficient from the reliability algorithm and/or equation.In some embodiments, the reliability algorithm and/or equation cancomprise an equation for calculation of Cronbach's α.

In some embodiments, a single reliability coefficient can be calculatedfor the form, and in some embodiments, a plurality of reliabilitycoefficients can be calculated for the form. In one embodiment, forexample, a plurality of reliability coefficients can be calculated forthe form based on variations of user attributes such as, for example,age, gender, language, education level, or the like. In someembodiments, a plurality of reliability coefficients can be calculatedthat can include, a reliability coefficient of the form and one orseveral reliability coefficients for portions of the form. In someembodiments, for example, the form may address a plurality of topics,behaviors, or the like. In such an embodiment, a reliability coefficientcan be calculated for each or some or all of the plurality of topics,behaviors, or the like. In such an embodiment, the calculation of thesereliability coefficients can include, for example, the identification oftopics, behaviors, or the like addressed by a form. The identificationof data packets associated with each of some or all of those identifiedtopics, behaviors, or the like, can include retrieval of metadata ofeach of the data packets and ascertaining association of the datapackets with the topics, behaviors, or the like based on the retrievedmetadata. After the association of data packets with topics, behaviors,or the like has been determined, metadata for data packets associatedwith a topic, behavior, or the like can be retrieved and gathered andcan be used in calculating a reliability coefficient for that topic,behavior, or the like.

After the content aggregation has been evaluated, the process 750proceeds to block 772, wherein the content score is compared to athreshold. In some embodiments, the threshold can delineate betweenacceptable reliability coefficients and unacceptable reliabilitycoefficients. In some embodiments, the threshold can comprise a singlethreshold, and in some embodiments, the threshold can comprise aplurality of thresholds. In some embodiments, for example in which areliability coefficients are calculated for the whole form and forportions of the form, a first threshold may be applied to thereliability coefficient for the form and one or several additionalthresholds may be applied to reliability coefficients for portions ofthe form.

The threshold can be retrieved from the database server 104 andspecifically from the threshold database 310. The response processor 678can compare the reliability coefficient to the threshold to determine ifthe reliability coefficient is acceptable or unacceptable. In someembodiments, the response processor 678 can associated a first valuewith the content aggregation or portion of the content aggregation ifcomparison of the reliability coefficient to the threshold indicatesthat the reliability coefficient is acceptable and a second value withthe content aggregation or portion of the content aggregation ifcomparison of the reliability coefficient to the threshold indicatesthat the reliability coefficient is unacceptable.

After the content score has been compared to the threshold, the process750 proceeds to decision state 774, wherein it is determined if thethreshold has been exceeded by the content score. In some embodiments,this determination can be based on the results of the comparison of thecontent score and the threshold. In some embodiments, this can includedetermining if the first value or if the second value is associated withthe content aggregation or portion of the content aggregation associatedwith the reliability coefficient. The decision at decision state 774 canbe performed by the one or several servers 102, the response processor678, the interface module 492 and/or the design interface module 496.

If it is determined that the content score is acceptable, then theprocess 750 proceeds to block 776, wherein the content aggregation isstored. In some embodiments, the content aggregation can be stored inthe database server 104, and specifically within the content librarydatabase 303 of the database server 104.

Returning again to decision state 774, if it is determined that thereliability coefficient is unacceptable, then the process 750 proceedsto block 778, wherein a compliance recommendation is generated. In someembodiments, the compliance recommendation can comprise a recommendationfor a change to the content aggregation. In some embodiments, thischange can include the addition of one or several data packets to thecontent aggregation, the removal of one or several packets from thecontent aggregation, or the like. In some embodiments, the compliancerecommendation can comprise a proposed change to the contentaggregation, which change would result in an increase in the reliabilitycoefficient and/or the meeting and/or exceeding of the threshold by thereliability coefficient when the content aggregation is modifiedaccording to the compliance recommendation. In some embodiments, thecompliance recommendation can be generated by the response processor678, the form application, and/or any other component or module of thecontent distribution network 100.

The generation of the compliance recommendation can comprise anevaluation of the content components of the content aggregation toidentify one or several content components with significant contributionto the unsatisfactory reliability coefficient. In some embodiments, thiscan include determining, for some or all of the content components,whether each content component increased or decreased the reliability ofthe content aggregation or of the portion of the content aggregation. Insome embodiments, this can further include determining whether othercontent components increase the reliability of the content aggregationor of the portion of the content aggregation by their addition to thecontent aggregation and/or by their replacing content components of thecontent aggregation.

In some embodiments, the generation of the compliance recommendation caninclude comparing the content aggregation to one or several of thepotential groupings identified in block 762. In some embodiments, thiscomparison can identify and/or indicate differences between the contentaggregation and one or several of the potential groupings. Thesedifferences can be evaluated to rank the differences from greatestimpact on the reliability coefficient to least impact on the reliabilitycoefficient. In some embodiments, some or all of these identifieddifferences and the content components associated with these identifieddifferences are the compliance recommendation.

After the compliance recommendation has been generated, the process 750proceeds to block 780, wherein the compliance recommendation is sent,and in some embodiments is sent to the supervisor device 110. Thecompliance recommendation can be sent to the supervisor device 110 bythe form application, the interface module 492 and/or the designinterface module 496. In some embodiments, the compliance recommendationcan be provided to the supervisor device 110 in the form of an alertthat can be generated and sent to the supervisor device 110 via thecommunications network 120. In some embodiments, the alert can include alink that, when selected, launches the application or navigates aweb-browser of the device of the selector of the link to page or portalassociated with the alert.

With reference now to FIG. 15, a flowchart illustrating one embodimentof a process 800 for automated data tracker delivery. The process 800can be performed by all or portions of the content distribution network100 and specifically by all or portions of the automatic contentremediation notification system 490. The process 800 begins at block802, wherein a content provision request is received. In someembodiments, the content provision request can be received by thesupervisor device 110, the interface module 492, the administratormodule 494, and/or the design interface module 496 from the supervisordevice 110. In some embodiments, the content provision request canidentify a recipient user for receipt of a content aggregation.

After the provision request has been received, the process 800 proceedsto block 804, wherein a content aggregation identifier is received. Insome embodiments, the content aggregation identifier can identify thecontent aggregation for providing to the recipient user. The contentaggregation identifier can be received by the supervisor device 110, theinterface module 492, the administrator module 494, and/or the designinterface module 496 from the supervisor device 110.

After the content aggregation identifier has been received, the process800 proceeds to block 806, wherein the content aggregation is selectedand/or retrieved. In some embodiments, this can be performed by thesupervisor device 110, the interface module 492, the administratormodule 494, and/or the design interface module 496. The contentaggregation can be selected and/or retrieved by querying the contentlibrary database 303 for the content aggregation corresponding to thereceived content aggregation identifier.

After the content aggregation has been selected and/or retrieved, theprocess 800 proceeds to block 808, wherein the content aggregation isprovided. In some embodiments, the content aggregation can be providedby the supervisor device 110, the interface module 492, theadministrator module 494, and/or the design interface module 496 to thesupervisor device 110 via the communication network 120.

After the content aggregation has been provided, the process 800proceeds to block 810, wherein response data is received. In someembodiments, the response data can be received by the supervisor device110, the interface module 492, the administrator module 494, and/or thedesign interface module 496 from the supervisor device 110 in responseto the provided content aggregation. In some embodiments, the responsedata can comprise data corresponding to user provided inputs respondingto some or all of the data packets in the content aggregation.

After the response data has been received, the process 800 proceeds toblock 812, wherein outcome data is generated. In some embodiments, thiscan include providing the received response data to the responseprocessor 678 and the response processor 678 evaluating the receivedresponse data. In some embodiments, the response processor 678 cangenerate a score characterizing the response data. In some embodiments,this score characterizing the response data can be based in part on theone or several additional statistical parameters generated with respectthe norm group of the content aggregation. In some embodiments, this caninclude characterizing the response data with respect to, for example,the mean and/or the standard deviation of the norm group. In someembodiments, this calculated score can comprise a standardized scoresuch as, for example, a T-score.

After the outcome data has been generated, the process 800 proceeds toblock 814, wherein the recipient user data is updated. In someembodiments this can be performed by the supervisor device 110, theinterface module 492, the administrator module 494, and/or the designinterface module 496. In some embodiments, this can include updating oneor several attributes of the user profile and/or data relating to therecipient user stored in the database server 104, and specifically withthe user profile database 301.

After the recipient user data has been updated, the process 800 proceedsto block 816, wherein a data tracker is generated. In some embodiments,the data tracker can be generated by the one or several servers 102, theinterface module 492, the administrator module 494, the design interfacemodule 496, and/or the response processor 678. The data tracker can begenerated based on the response data received in block 810 as well asany other previously received relevant response data. In someembodiments, for example, a plurality of content aggregations can beprovided to the recipient user over a period of time to track therecipient user's progress. In some embodiments, this progress can relateto how the recipient user is developing a skill, an attribute, or thelike. In some embodiments, this progress can relate to whether and/orthe degree to which the recipient user is changing a habit or tendency,developing a habit or tendency, or the like. In some embodiments, thisprogress can relate to changes in the recipient user with respect to oneor several metrics measured by the content aggregation.

One embodiment of the data tracker 900 is shown in FIG. 16. The datatracker 900 can comprise a graphical depiction of user progress overtime. The data tracker 900 can include a first axis 902 that canidentify score data and a second axis 904 that can identify date data.The data tracker 900 can further include a tracking line 906 that canidentify one or several data points generated from responses provided bythe recipient user to content aggregations over time.

The data tracker 900 can, in some embodiments, include a time-marker 908that, in some embodiments, identify when an intervention was provided.As seen in FIG. 16, the time-marker 908 delineates between datacollected before, for example, the intervention and data collected afterthe intervention. In some embodiments, this time marker can facilitatein determining the effectiveness of the provided intervention.

The data tracker 900 can include a first zone 910 and a second zone 912.In some embodiments, each of the first zone 910 and the second zone 912can correspond to a set of scores. In some embodiments, for example, thefirst zone 910 corresponds to scores indicating an “at-risk” state inwhich the recipient user is at risk of an adverse outcome. In someembodiments, the second zone 912 corresponds to scores identifying a“goal zone” in which the recipient user is at lower risk of the adverseoutcome. In some embodiments, the first zone 910 can be indicated with afirst color and/or pattern and the second zone 912 can be indicated witha second color and/or pattern.

The data tracker can include a data portion 914 that can provide datacorresponding to the data identified with the tracking line 906 and/orin addition to the data identified with the tracking line 906. In someembodiments, for example, the data portion can include a T score, a rawscore, a value identifying a change from the earliest score, dataindicating a statistical significance of the change from the earliestscore, a value identifying a change from the immediately previous score,and/or a value indicating a statistical significance of the change fromthe immediately previous score. In some embodiments, the scores and/ordata contained in the data tracker 900 can be generated by the responseprocessor 678 and/or another component of the automatic contentremediation notification system 490.

Returning again to process 800, after the data tracker 900 has beengenerated, the data tracker 900 can be provided as indicated in block818. In some embodiments, the data tracker can be provided to thesupervisor device 110 in the form of an alert that can be generated andsent to the supervisor device 110 from the one or several servers 102 ormore specifically from the interface module 492, the administratormodule 494, and the design interface module 496 via the communicationsnetwork 120. In some embodiments, the receipt of the alert can result inthe launching of an application within the receiving device, and in someembodiments, the alert can include a link that, when selected, launchesthe application or navigates a web-browser of the device of the selectorof the link to page or portal associated with the alert

In some embodiments, this alert can be generated when, for example, thetracking line 906 crosses from the first zone 910 to the second zone912, or when the tracking line 906 fails to cross from the first zone910 to the second zone 912 within a specified time frame. In someembodiments, for example, the amount of time passed since time-marker908 can be tracked. If this amount of time is greater than a thresholdvalue, then an alert can be generated and sent, as discussed herein, tothe user device 106 and/or to the supervisor device 110. In someembodiments, the alert can be sent to the creator of the form or formsfrom which the tracking line 906 is generated, or to the person whoassigned the form or forms from which the tracking line 906 isgenerated. In some embodiments, this alert can include informationrelating to one or several potential interventions and/or recommendingone or several interventions.

A number of variations and modifications of the disclosed embodimentscan also be used. Specific details are given in the above description toprovide a thorough understanding of the embodiments. However, it isunderstood that the embodiments may be practiced without these specificdetails. For example, well-known circuits, processes, algorithms,structures, and techniques may be shown without unnecessary detail inorder to avoid obscuring the embodiments.

Implementation of the techniques, blocks, steps and means describedabove may be done in various ways. For example, these techniques,blocks, steps and means may be implemented in hardware, software, or acombination thereof. For a hardware implementation, the processing unitsmay be implemented within one or more application specific integratedcircuits (ASICs), digital signal processors (DSPs), digital signalprocessing devices (DSPDs), programmable logic devices (PLDs), fieldprogrammable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described above, and/or a combination thereof.

Also, it is noted that the embodiments may be described as a processwhich is depicted as a flowchart, a flow diagram, a swim diagram, a dataflow diagram, a structure diagram, or a block diagram. Although adepiction may describe the operations as a sequential process, many ofthe operations can be performed in parallel or concurrently. Inaddition, the order of the operations may be re-arranged. A process isterminated when its operations are completed, but could have additionalsteps not included in the figure. A process may correspond to a method,a function, a procedure, a subroutine, a subprogram, etc. When a processcorresponds to a function, its termination corresponds to a return ofthe function to the calling function or the main function.

Furthermore, embodiments may be implemented by hardware, software,scripting languages, firmware, middleware, microcode, hardwaredescription languages, and/or any combination thereof. When implementedin software, firmware, middleware, scripting language, and/or microcode,the program code or code segments to perform the necessary tasks may bestored in a machine readable medium such as a storage medium. A codesegment or machine-executable instruction may represent a procedure, afunction, a subprogram, a program, a routine, a subroutine, a module, asoftware package, a script, a class, or any combination of instructions,data structures, and/or program statements. A code segment may becoupled to another code segment or a hardware circuit by passing and/orreceiving information, data, arguments, parameters, and/or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

For a firmware and/or software implementation, the methodologies may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing themethodologies described herein. For example, software codes may bestored in a memory. Memory may be implemented within the processor orexternal to the processor. As used herein the term “memory” refers toany type of long term, short term, volatile, nonvolatile, or otherstorage medium and is not to be limited to any particular type of memoryor number of memories, or type of media upon which memory is stored.

Moreover, as disclosed herein, the term “storage medium” may representone or more memories for storing data, including read only memory (ROM),random access memory (RAM), magnetic RAM, core memory, magnetic diskstorage mediums, optical storage mediums, flash memory devices and/orother machine readable mediums for storing information. The term“machine-readable medium” includes, but is not limited to portable orfixed storage devices, optical storage devices, and/or various otherstorage mediums capable of storing that contain or carry instruction(s)and/or data.

While the principles of the disclosure have been described above inconnection with specific apparatuses and methods, it is to be clearlyunderstood that this description is made only by way of example and notas limitation on the scope of the disclosure.

What is claimed is:
 1. A system for automatic content remediationnotification comprising: memory comprising: a content library database,wherein the content library database comprises: a plurality of datapackets; and metadata associated with each of the data packets, whereinthe metadata identifies at least one attribute of the associated datapacket; a first user device comprising: a first network interfaceconfigured to exchange data via a communication network; and a first I/Osubsystem configured to convert electrical signals to user interpretableoutputs via a user interface; a second user device; and one or moreservers, wherein the one or more servers are configured to: receive acontent aggregation creation request from the first user device;identify content information associated with a set of the plurality ofdata packets in response to the receipt of the content aggregationcreation request; apply a filter request to the set of the plurality ofdata packets to form a restricted set of data; automatically provideinformation relating to data packets in the restricted set of datapackets to the first user device; receive content aggregate informationidentifying a content aggregate from the first user device, wherein thecontent aggregate comprises a plurality of data packets from therestricted set of data packets; evaluate the content aggregate accordingto the metadata associated with the data packets of the contentaggregate; and automatically output an indicator of the evaluationresult to the first user device.
 2. The system of claim 1, wherein theone or more servers are further configured to receive a filter requestfrom the first user device, wherein the filter request identifies atleast one attribute as a criterion for inclusion of a data packet withinthe restricted set of data packets.
 3. The system of claim 2, whereinthe filter request identifies an intended recipient of the contentaggregate.
 4. The system of claim 3, wherein the identification of theintended recipient of the content aggregate comprises identification ofone or more attributes of the intended recipient of the contentaggregate.
 5. The system of claim 3, wherein applying the filter requestto the set of the plurality of data packets comprises identifying a normgroup for the intended recipient.
 6. The system of claim 5, wherein thenorm group comprises norm data previously gathered from users similar tothe intended recipient.
 7. The system of claim 6, wherein evaluating thecontent aggregate comprises automatically generating a reliability valuebased on the metadata of the data packets in the content aggregate. 8.The system of claim 7, wherein the reliability value comprise Cronbach'sα.
 9. The system of claim 7, wherein the reliability value is generatedfor at least one age group.
 10. The system of claim 7, whereinevaluating the content aggregate further comprises generatingsupplemental statistical parameters from the norm group data.
 11. Thesystem of claim 10, wherein the supplemental statistical parameterscomprise a mean and a standard deviation.
 12. The system of claim 10,evaluating the content aggregate further comprises: generating a contentscore; comparing the content score to a threshold, wherein the thresholddelineates between acceptable and unacceptable content scores; andgenerating a compliance recommendation when the comparing of the contentscore to the threshold indicates that the content score is unacceptable.13. The system of claim 12, wherein the compliance recommendationidentifies at least one data packet for inclusion in the contentaggregation.
 14. The system of claim 13, wherein automaticallyoutputting the indicator of the evaluation result comprisesautomatically sending the compliance recommendation to the first userdevice.
 15. A method for automatic content remediation notificationcomprising: receiving a content aggregation creation request from thefirst user device; identifying content information associated with a setof the plurality of data packets in response to the receipt of thecontent aggregation creation request; applying a filter request to theset of the plurality of data packets to form a restricted set of data;automatically providing information relating to data packets in therestricted set of data packets to the first user device; receivingcontent aggregate information identifying a content aggregate from thefirst user device, wherein the content aggregate comprises a pluralityof data packets from the restricted set of data packets; evaluating thecontent aggregate according to the metadata associated with the datapackets of the content aggregate; and automatically outputting anindicator of the evaluation result to the first user device.
 16. Themethod of claim 15, further comprising receiving a filter request from afirst user device, wherein the filter request identifies at least oneattribute as a criterion for inclusion of a data packet within therestricted set of data packets, wherein the filter request identifies anintended recipient of the content aggregate.
 17. The method of claim 16,wherein the identification of the intended recipient of the contentaggregate comprises identification of one or more attributes of theintended recipient of the content aggregate, and wherein applying thefilter request to the set of the plurality of data packets comprisesidentifying a norm group for the intended recipient, wherein the normgroup comprises norm data previously gathered from users similar to theintended recipient.
 18. The method of claim 17, wherein evaluating thecontent aggregate comprises automatically generating a reliability valuebased on the metadata of the data packets in the content aggregate andgenerating supplemental statistical parameters from the norm group data.19. The method of claim 18, wherein evaluating the content aggregatefurther comprises: generating a content score; comparing the contentscore to a threshold, wherein the threshold delineates betweenacceptable and unacceptable content scores; and generating a compliancerecommendation when the comparing of the content score to the thresholdindicates that the content score is unacceptable.
 20. The method ofclaim 19, wherein the compliance recommendation identifies at least onedata packet for inclusion in the content aggregation, and whereinautomatically outputting the indicator of the evaluation resultcomprises automatically sending the compliance recommendation to thefirst user device.